relyt0925 · July 8, 2024 01:42
diff --git a/sdggeneratefullrun.log b/sdggeneratefullrun.log
 knowledge/technical_manual/ibm_redbooks/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/knowledge/technical_manual/ibm_redbooks/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/knowledge/technical_manual/ibm_redbooks --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T20:39:05Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/knowledge/technical_manual/ibm_redbooks/qna.yaml' against http://0.0.0.0:8080/v1 server
 Traceback (most recent call last):
  File "/usr/local/lib/python3.11/site-packages/instructlab/utils.py", line 538, in read_taxonomy_file
    documents = get_documents(source=documents, logger=logger)
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/instructlab/utils.py", line 225, in get_documents
    raise e
  File "/usr/local/lib/python3.11/site-packages/instructlab/utils.py", line 206, in get_documents
    repo = git_clone_checkout(
           ^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/instructlab/utils.py", line 231, in git_clone_checkout
    repo = Repo.clone_from(repo_url, temp_dir)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/git/repo/base.py", line 1525, in clone_from
    return cls._clone(
           ^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/git/repo/base.py", line 1396, in _clone
    finalize_process(proc, stderr=stderr)
  File "/usr/local/lib/python3.11/site-packages/git/util.py", line 504, in finalize_process
    proc.wait(**kwargs)
  File "/usr/local/lib/python3.11/site-packages/git/cmd.py", line 834, in wait
    raise GitCommandError(remove_password_if_present(self.args), status, errstr)
 git.exc.GitCommandError: Cmd('git') failed due to: exit code(128)
  cmdline: git clone -v -- <document-repository-url-goes-here> /tmp/tmpeno7f9vv
  stderr: 'fatal: repository '<document-repository-url-goes-here>' does not exist
 '

 The above exception was the direct cause of the following exception:

 Traceback (most recent call last):
  File "/usr/local/bin/ilab", line 8, in <module>
    sys.exit(ilab())
             ^^^^^^
  File "/usr/local/lib/python3.11/site-packages/click/core.py", line 1157, in __call__
    return self.main(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/click/core.py", line 1078, in main
    rv = self.invoke(ctx)
         ^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/click/core.py", line 1688, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/click/core.py", line 1434, in invoke
    return ctx.invoke(self.callback, **ctx.params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/click/core.py", line 783, in invoke
    return __callback(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/click/decorators.py", line 33, in new_func
    return f(get_current_context(), *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/instructlab/data/generate.py", line 198, in generate
    generate_data(
  File "/usr/local/lib/python3.11/site-packages/instructlab/data/generator/generate_data.py", line 392, in generate_data
    seed_instruction_data = utils.read_taxonomy(
                            ^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/instructlab/utils.py", line 566, in read_taxonomy
    seed_instruction_data, warnings, errors = read_taxonomy_file(
                                              ^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/instructlab/utils.py", line 557, in read_taxonomy_file
    raise TaxonomyReadingException(f"Exception {e} raised in {file_path}") from e
 instructlab.utils.TaxonomyReadingException: Exception Cmd('git') failed due to: exit code(128)
  cmdline: git clone -v -- <document-repository-url-goes-here> /tmp/tmpeno7f9vv
  stderr: 'fatal: repository '<document-repository-url-goes-here>' does not exist
 ' raised in /instructlab/taxonomytar/taxonomy/knowledge/technical_manual/ibm_redbooks/qna.yaml
 knowledge/textbook/history/ibm_history/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/knowledge/textbook/history/ibm_history/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/knowledge/textbook/history/ibm_history --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T20:39:15Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/knowledge/textbook/history/ibm_history/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 20:39:29,249 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Discover the timeline of Thomas J. Watson's journey from branch manager to taking the reins at the Computing-Tabulating-Recording Company (C-T-R).
 I> 
 A> Thomas J. Watson's career progression towards taking the helm of C-T-R began with his entry-level role at the National Cash Register, where he quickly rose to the position of branch manager in just a few years. In 1914, Charles Flint hired Watson as general manager of C-T-R, and following the dismissal of a lawsuit in which he was implicated, Watson was formally appointed as president in 1915. Under his leadership, the company underwent significant transformations and emerged as the thriving International Business Machines.

 Q> What was the role of Thomas J. Watson in the creation and transformation of C-T-R into a successful company?
 I> 
 A> Thomas J. Watson played a crucial role in the creation and transformation of C-T-R into a successful company by focusing resources on the tabulating machine, while de-emphasizing the scale and time clock. He implemented strategic changes and expanded operations internationally. In 1924, Watson changed the company's name to International Business Machines, positioning it as a prominent player in the information technology field. Furthermore, Watson instilled philosophies that remain core components of IBM's identity today.


  2% 2/100 [00:11<09:20,  5.72s/it]INFO 2024-06-26 20:39:40,685 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> How did the globally distinctive identity of IBM come to be during Thomas J. Watson's tenure as CEO?
 I> 
 A> During his tenure as CEO of IBM, Thomas J. Watson played a crucial role in shaping the company's global identity. Under his guidance, IBM developed a strong culture focusing on customer service and sales, employment benefits, and system sales strategies that propelled the company to the forefront of the technology industry and fostered a consistent, globally recognized image for IBM.

 Q> What made the Hollerith Tabulating Machine essential to businesses during the early 1900s?
 I> 
 A> The Hollerith Tabulating Machine became essential to businesses in the early 1900s due to its ability to gather and analyze data systematically using a hole-punch system and cards. This versatile technology streamlined data collection, making it a valuable asset to businesses dealing with customer records, train traffic, and insurance.


  4% 4/100 [00:21<08:35,  5.37s/it]INFO 2024-06-26 20:39:50,933 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Explain the history and significance of the International Time Recording Company (ITR) in the formation of IBM.
 I> 
 A> The International Time Recording Company, also known as ITR, was a significant player in the early formation of IBM, with roots going back to the Bundy Manufacturing Company and its time recording business. George W. Fairchild, who played a pivotal role in the creation of ITR, later served as the president of the company and facilitated its merger with two other firms in 1911 to form the Computing-Tabulating-Recording Company. Eventually becoming IBM, this merger owed much of its success to the solid foundation laid by ITR, particularly in the realm of accurate information processing related to time.

 Q> Identify, describe, and elaborate on the challenges businesses faced in the early 20th century that led to the creation and success of the International Time Recording Company (ITR).
 I> 
 A> In the early 20th century, businesses faced a daunting challenge in accurately measuring and expressing the passage of time to enhance payroll processing. Prior manual methods for recording time and attendance were often prone to inaccuracies, human error, and inefficient paper-based systems that inhibited productivity. The arrival of the International Time Recording Company (ITR), led by the Bundy Key Recorder invention in 1888, revolutionized time-tracking. ITR's innovative products, which included the Rochester Recorder, eliminated significant challenges for businesses by providing a card-based system to record attendance, reducing disputes, and increasing the efficiency of payroll processing. This groundbreaking technology led to the rapid growth and success of ITR and its influence on the formation of IBM.


  6% 6/100 [00:33<08:49,  5.64s/it]INFO 2024-06-26 20:40:02,848 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> What was the initial purpose of the tabulating machine and how did businesses find additional uses for this technology?
 I> 
 A> Initially, the tabulating machine was designed by Herman Hollerith to help the US Census Bureau collect data on the country’s expanding population using a pattern of holes in cardboard cards to represent individual’s data, such as city of residence, age, nationality, and job. Businesses later discovered that the tabulator’s hole-punch system could provide valuable information on products, train traffic, and insurance customers, with early adopters including the freight office of the New York Central Railroad and the Eastman Kodak Company.


  7% 7/100 [00:39<08:40,  5.60s/it]INFO 2024-06-26 20:40:08,337 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Explain how Herman Hollerith's innovation of the punched card system led to the development of computers and the binary system of zeros and ones.
 I> 
 A> Herman Hollerith's invention of the punched card tabulator laid the foundation for modern computers and the binary system of zeros and ones. This electromechanical system used punched cards to store and process data through electric circuits. The opening or closing of the holes in cards transmitting electrical signals created a binary system that is fundamental to digital computing. Over the years, the punched card system was adapted and improved, eventually leading to the development of electronic digital computers.

 Q> Describe the motivation behind Herman Hollerith's invention of the punched card tabulator for the US Census process.
 I> 
 A> Herman Hollerith invented the punched card tabulator to automate the US Census process due to the frustration he experienced with the manual, error-prone labor involved in counting questionnaires. The overtaxed Census Office presented a significant challenge, but he believed that automation was the answer. This invention resulted in a machine that not only eased the administrative burden of hand-counting rapidly growing populations but also laid the foundation for mechanized data processing and the computing industry.


  9% 9/100 [00:50<08:36,  5.67s/it]INFO 2024-06-26 20:40:19,899 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> What changes did Thomas J. Watson implement on the product focus and company name while at the helm of IBM?
 I> 
 A> Thomas J. Watson made notable changes to the product focus and company name during his time as IBM's CEO. To sense and meet imminent demand, Watson shifted IBM's resources towards the tabulating machine, de-emphasizing lesser-promising products like the scale and time clock. This product focus shift led to a four-year revenue doubling for IBM, and following successful international expansion, the company was renamed International Business Machines (IBM) in 1924.

 Q> Summarize Thomas J. Watson's professional journey before his tenure at IBM and the company's primary focus during his leadership.
 I> 
 A> Thomas J. Watson, prior to leading IBM, was a born salesman who worked his way up to an entry-level role at National Cash Register and rose quickly to a branch manager within a few years. Upon joining C-T-R as general manager in 1914, Watson redirected the company's resources to prioritize the tabulating machine, immediately feeling its potential. By de-emphasizing the scale and time clock, Watson successfully doubled C-T-R's revenues within four years and set the stage for a stronger, global presence.


 11% 11/100 [01:02<08:34,  5.78s/it]INFO 2024-06-26 20:40:31,795 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Investigate the short stint that Herman Hollerith undertook at the US Census Office and how it catalyzed his invention.
 I> 
 A> Herman Hollerith's brief tenure at the US Census Office in the 1880s proved to be a pivotal moment that fueled his passion for automation and invention. Frustrated by the labor-intensive manual counting of questionnaires, an idea to develop an electric-powered counting machine dawned upon him. This invention would soon revolutionize data processing, paving the way for the development of computers and the binary system used in modern information processing.

 Q> Uncover the concept and inspiration behind Herman Hollerith's punched card system that impressed the census authorities.
 I> 
 A> Herman Hollerith's punched card system, implemented in the 1880s, was a remarkable achievement inspired by a few unique ideas. Around 80 years prior, Joseph Marie Jacquard devised a system using punched cards to automate steam-powered weaving looms. In the 1830s, English mathematician Charles Babbage had developed plans for a computing engine that relied on punched cards for instructions. Building on these concepts, Hollerith applied the principle to data processing in his quest to create a system to capture and compile census information. This innovation showcased his ability to look beyond conventional data handling methods and implement cutting-edge technology to streamline and automate the process.


 13% 13/100 [01:15<08:36,  5.94s/it]INFO 2024-06-26 20:40:44,272 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Explain the background of Charles Ranlett Flint and the reason he is considered the "Father of Trusts."
 I> 
 A> Charles Ranlett Flint was a financier and businessman who established a reputable career by merging companies in industries such as rubber and wool, gaining the nickname "Father of Trusts." Before focusing on information technologies, Flint invested in diverse sectors and facilitated multi-company mergers. His strategic foresight and skill in combining enterprises ultimately set the stage for the creation of IBM.

 Q> Discuss the role of the tabulating machine in the U.S. Census Bureau and its impact on the organization.
 I> 
 A> The tabulating machine was originally invented by Herman Hollerith to ease data collection for the US Census Bureau. Adopted by various international census agencies, it significantly reduced the time and cost required to process census data. The machine's invention proved invaluable in dealing with the rapidly expanding population, saving the American government two years and USD 5 million during the 1890 census.


 15% 15/100 [01:25<08:09,  5.75s/it]INFO 2024-06-26 20:40:55,038 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Describe the function and role of the Bundy Key Recorder in the development of IBM's Time Equipment Division.
 I> 
 A> The Bundy Key Recorder, launched in 1888, was a mechanical time recorder that played a crucial role in the formation of IBM's Time Equipment Division. This innovation significantly decreased inaccuracies and disputes in payroll processing by printing the exact time and an employee's number on a paper tape when the employee inserted a specially-designed key. This pioneering device revolutionized time-tracking methods and laid the foundation for the expansion and growth of the division.

 Q> List the noteworthy inventions that contributed to IBM's Time Equipment Division's early success.
 I> 
 A> Three major inventions contributed to the early success of IBM's Time Equipment Division:
 1. Bundy Key Recorder (1888): A mechanical time recorder that substantially minimized inaccuracies and arguments in payroll processing, thanks to its ability to print employees' numbers and exact times on paper tape when their specially-designed keys were inserted.
 2. Dey Dial Recorder (1888): This time recording device featured a large ring with employee numbers around the circumference. Employees could pivot a pointer arm to their number and press it into a guide hole at the start and end of each shift, thereby printing the time on a sheet within the machine.
 3. Rochester Recorder (1894): Devised by Daniel M. Cooper, this world's first card-based system to record attendance worked by using a printed card divided into seven spaces representing the days of the week. When an employee inserted a card and pressed a lever, the time was printed in the appropriate "In" or "Out" slot.


 17% 17/100 [01:38<08:12,  5.94s/it]INFO 2024-06-26 20:41:07,681 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Describe the challenges faced by the US Census Office before the adoption of Hollerith's punched card tabulator and how it improved the process.
 I> 
 A> Before the adoption of Herman Hollerith's punched card tabulator, the US Census Office was burdened with the tedious and error-prone task of manually counting questionnaires for their data processing. The overwhelming workload put a strain on the overtaxed agency, as the manual method was time-consuming and prone to operational nightmares due to the extensive labor involved. After the introduction of the punched card tabulator, the administrative burden of hand-counting the exploding population was significantly eased, resulting in a more efficient and accurate count. This success also led to the adoption of the tabulator in other countries for national counts and private businesses for statistical and accounting purposes.

 Q> Explain the role of Charles Babbage in the development of punched card technology and the Analytical Engine.
 I> 
 A> Charles Babbage played an essential role in the development of punched card technology during the mid-1830s with his plans for the Analytical Engine. Although he didn't invent punched cards, Babbage saw their potential and employed them to automate his computing engine and enable its mathematical calculations. The Analytical Engine, often considered a forerunner of modern computers, illustrates how Babbage recognized the utility of punched cards and innovatively applied their binary principles to develop more sophisticated technology.


 19% 19/100 [01:50<08:02,  5.95s/it]INFO 2024-06-26 20:41:19,670 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Describe Charles Ranlett Flint's business approach and how it shaped IBM's early years.
 I> 
 A> Charles Ranlett Flint was a financier and businessman known for his mergers and consolidations, earning the moniker "Father of Trusts." In IBM's early years, Flint used this approach by merging three data-processing companies, creating the Computing-Tabulating-Recording company (later IBM). This move brought together complementary technologies (time clock, computing scale, and tabulating machine) from various companies, strategically positioning IBM as a significant player in information technology. The early years of IBM were deeply shaped by Flint's understanding of melding industries and adopting emerging technologies.

 Q> Discuss the significance of the merger between the International Time Recording Company, Computing Scale Company, and Tabulating Machine Company in 1911.
 I> 
 A> The merger of the International Time Recording Company, Computing Scale Company, and Tabulating Machine Company in 1911 was significant as it united enterprises that specialized in complementary data-processing technologies. This merger formed the Computing-Tabulating-Recording Company, which would later become IBM. The consolidation enabled these companies to expand their markets, share resources, and harness their competitive advantages. This merger was a focal point in the evolution of data and technology processing industries, considering the significant impact it had on both the private and public sectors.


 21% 21/100 [02:01<07:43,  5.87s/it]INFO 2024-06-26 20:41:31,033 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> How did Herman Hollerith's experience as a mining engineer and his exposure to Joseph Marie Jacquard's punch card system influence his invention of the punched card tabulator?
 I> 
 A> Herman Hollerith's background in mining engineering and his exposure to the punch card system designed by Joseph Marie Jacquard for automated steam-powered weaving looms were instrumental in the creation of the punched card tabulator. The frustrations he faced while compiling manufacturing statistics for the US Census Office inspired him to design an electromechanical system that could automate data processing and reduce human error. By adapting the punched card concept and integrating it with electric circuits, he successfully developed a groundbreaking technology that transformed the way information was processed and stored, eventually leading to the modern computer age.

 Q> Describe the competitive process that Hollerith went through to secure the contract for processing the 1890 US census and the impact of his victory on the evolution of his invention.
 I> 
 A> In 1888, Herman Hollerith entered a competition organized by the Census Office to find the fastest tabulating solution for the 1890 US census. He faced two competitors, one of whom required 144.5 hours and the other 100.5 hours to process the needed data. Hollerith triumphed with a processing time of 72.5 hours and demonstrated a superior ability to prepare data for tabulation, clocking in at a remarkable 5.5 hours as opposed to his competitors' times of 44.5 and 55.5 hours. By winning the competition, Hollerith secured the contract for processing the 1890 US census, which led to refining and improving his invention for years to come, creating variations of the tabulator that would impact business and society for decades.


 23% 23/100 [02:14<07:42,  6.00s/it]INFO 2024-06-26 20:41:43,630 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> How did Thomas J. Watson's marketing philosophy contribute to IBM's success and dominance in information technology?
 I> 
 A> Thomas J. Watson recognized the potential of a unified marketing strategy and integrated marketing and sales principles throughout IBM. He emphasized identifying customer needs, providing complete solutions, and proactively establishing sales training and public relations strategies. This cohesive thinking resulted in IBM's success and dominance in various stages of information technology. Watson's marketing philosophy, which encouraged personal connections with customers and providing long-term value, played a crucial role in IBM's global recognition and influence during its early years.

 Q> elucidate
 Describe how IBM's international operations began and evolved under the guidance of Thomas J. Watson.
 I> 
 A> IBM's international operations began under the leadership of Thomas J. Watson, who recognized early on that global expansion was critical for the company's future. In 1924, Watson renamed Computing-Tabulating-Recording to International Business Machines, reflecting its broader mission and a new strategic focus on international expansion. Under Watson's stewardship, IBM established foreign sales branches and subsidiaries in Europe and South America, which eventually allowed IBM to grow and expand into one of the most significant tech companies worldwide. IBM, the first major American company to embark on international operations, engaged in various global activities, from building Type 1403 printers in Japan in the 1960s to the early development of punch-card machines in Germany. The corporation's overseas ventures evolved IBM into a multi-billion-dollar organization.


 25% 25/100 [02:26<07:31,  6.02s/it]INFO 2024-06-26 20:41:55,728 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Find out how Herman Hollerith's invention of an electric-powered counting machine revolutionized data processing and sparked the development of computers.
 I> 
 A> Herman Hollerith's invention of an electric-powered counting machine, the punched card tabulator, led to major breakthroughs in data processing. This machine streamlined the tedious process of manual data handling by automating the counting of questionnaires and paved the way for the binary system of zeros and ones, which forms the basis for information processing today. The success of his invention caught the attention of various countries and private businesses, generating significant profits over several decades for IBM, originally known as the Computing-Tabulating-Recording Company (C-T-R).

 Q> Compare and contrast the processing times of Hollerith's punched card tabulator and his competitors' machines during the 1890 US census competition.
 I> 
 A> During the 1890 US census competition, Herman Hollerith's punched card tabulator proved to be considerably faster than those of his two competitors. The first competitor clocked in at 144.5 hours to capture the data used for the challenge, while the second competitor managed 100.5 hours. Hollerith's machine, however, demonstrated greater efficiency by logging a significantly shorter time of 72.5 hours. For data preparation and tabulation, Hollerith's machine recorded 5.5 hours, compared to 44.5 and 55.5 hours for his competitors, further emphasizing its superiority.


 27% 27/100 [02:38<07:18,  6.01s/it]INFO 2024-06-26 20:42:07,736 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> In what year and by whom was the Rochester Recorder, the world's first card-based system to record attendance, patented?
 I> 
 A> The Rochester Recorder was patented in 1894 by Daniel M. Cooper. This innovation became the world's first card-based system to record attendance, with a printed card representing the days of the week and time recorded in the appropriate "In" or "Out" slot.

 Q> What were the principal reasons behind IBM's decision to sell the Time Equipment Division in the late 1950s?
 I> 
 A> IBM's decision to sell the Time Equipment Division in the late 1950s was primarily driven by the growing incompatibility of the division's products with the operations of the company's expanding data processing and electric typewriter businesses. The shift in focus towards principle product lines allowed IBM to better serve the interests of its employees, stockholders, and customers.


 29% 29/100 [02:49<06:51,  5.80s/it]INFO 2024-06-26 20:42:18,326 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Describe how Joseph Marie Jacquard's invention influenced Herman Hollerith's development of the punched card system.
 I> 
 A> Joseph Marie Jacquard's invention of the punch-card-operated loom significantly influenced Herman Hollerith in developing the punched card system. Jacquard's invention demonstrated how punched cards could be used to automate complex processes. When designing his data processing machine, Hollerith recognized the potential in adapting Jacquard's concept for data storage and processing by punching holes in cards. By employing this idea, Hollerith brought about mechanized data processing, revolutionizing the census and ultimately contributing to the foundation of modern computing.

 Q> Summarize Herman Hollerith's journey to the successful development and implementation of his punched card system.
 I> 
 A> Herman Hollerith pioneered the electromechanical data processing system by inventing the punched card tabulator in the 1880s. Frustrated by the tedious and error-prone manual counting process, Hollerith was inspired to automate the census process. After being introduced to the concept of punched cards in weaving looms, he modified the idea to store data using holes punched into strips of paper. He later shifted to using punched cards, receiving two patents in 1889. He conducted preliminary tests in 1886, and his machine won a competition in 1888 at the US Census Office, securing the contract for the 1890 census. This success paved the way for punched card system use in multiple industries, with IBM eventually profiting exorbitantly over decades.


 31% 31/100 [03:01<06:53,  5.99s/it]INFO 2024-06-26 20:42:31,191 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Explain how Herman Hollerith's invention of the punched card tabulator was influenced by the work of Joseph Marie Jacquard and Charles Babbage.
 I> 
 A> Herman Hollerith's punched card tabulator was inspired by the work of French inventor Joseph Marie Jacquard and English mathematician Charles Babbage. Jacquard devised a method using punched cards for automating steam-powered weaving looms in the early 19th century. Later, Babbage proposed a computing engine that utilized punched cards for instructions. Building upon these previous innovations, Hollerith was the first to apply the punch card principle to data processing, easing the burden of the manual census process and leading to the foundation of modern information processing systems.

 Q> Describe the process of how the punched cards were transferred and sorted using Hollerith's machines for the US census from 1880 until the 1890 census.
 I> 
 A> For the US census, data was manually transferred onto punched cards from paper schedules by clerks using a hole puncher at a rate of 500 per day. These punched cards were then manually fed into a card reader, creating electric circuit connections between pins and a mercury reservoir when passing through open holes, which would register either a "1" or a "0" on dials based on demographic data. After tabulating, a separate machine sorted the cards into as many as 24 categories based on the holes' locations. A proficient operator could sort 80 cards a minute. This process significantly improved the census processing time and accuracy compared to the manual methods employed between 1880 and 1890.


 33% 33/100 [03:14<06:46,  6.06s/it]INFO 2024-06-26 20:42:43,674 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> What role did Thomas J. Watson play in restructuring the Computing-Tabulating-Recording (C-T-R) company, and which company name did it adopt under his leadership?
 I> 
 A> Thomas J. Watson, the future president of C-T-R, joined the company in 1914 as the general manager when it was still known by its original name. Watson de-emphasized certain products, like the scale and the time clock, while refocusing resources on the tabulating machine, speeding up the company's revenue growth. In under four years, C-T-R's revenue doubled. As part of his campaign of change and expansion, Watson renamed Computing-Tabulating-Recording to International Business Machines in 1924, further establishing the company's global presence.

 Q> Highlight some of the philosophies and worldviews IBM has retained since Watson's era in the technology and data processing industry.
 I> 
 A> During Watson's leadership at IBM, he shaped a unified company culture with several key philosophies and worldviews that have been retained within the technology and data processing industry. IBM has continued to emphasize globalism, embracing new challenges as a worldwide institution and fostering a presence in various international markets. Furthermore, the company pursues equal pay for equal work, irrespective of an employee's background. A notable hallmark of IBM's vision is the imperative to 'think,' emphasizing modern techniques against complacent reliance on older methods. These lasting values reinforce IBM's commitment to innovation and contribute to the company's enduring success.


 35% 35/100 [03:26<06:35,  6.08s/it]INFO 2024-06-26 20:42:56,085 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Find out the main companies involved in the development of C-T-R and the role each one played in the merger.
 I> 
 A> The three main companies involved in the development of C-T-R were the International Time Recording Company, the Computing Scale Company, and the Tabulating Machine Company. Charles Flint – the Father of Trusts – recognized the shared emphasis on data among these companies' respective products: time clocks, computing scales, and tabulating machines. He brought the leaders of these businesses together and merged them into the Computing-Tabulating-Recording Company in 1911. The International Time Recording Company provided time clocks for factory workers, the Computing Scale Company equipped businesses with weighing and cost-summing machines, and the Tabulating Machine Company attracted a marquee customer in the US Census Bureau with Herman Hollerith's tabulating machine technology.

 Q> Identify the challenges C-T-R faced at its inception, and how its subsequent success overcame those challenges.
 I> 
 A> C-T-R faced significant challenges at its inception, as the merger between the three founding companies in 1911 led to substantial debt and caused resentment among some of the original management teams. The resistance to full integration barred C-T-R from reaching its full potential in the initial years of its operations. However, Thomas J. Watson's arrival as the company's CEO marked a turning point for C-T-R. His leadership brought about a unifying culture emphasizing customer service, sales, and sales strategies. This new strategic direction provided the company with momentum, enabling it to move past earlier challenges and transform into the thriving global behemoth in technology, management, and culture, known as International Business Machines (IBM).


 37% 37/100 [03:39<06:30,  6.19s/it]INFO 2024-06-26 20:43:08,809 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Describe the three inventions that made the International Time Recording Company, a progenitor of IBM, so successful between 1888 and 1914.
 I> 
 A> Three inventions led to the success of the International Time Recording Company, a critical precursor to IBM:

 1. The Bundy Key Recorder (1888), which minimized inaccuracies and disputes in payroll processing by printing exact times and employee numbers on a paper tape.
 2. The Dial Recorder (1888) by Alexander Dey, featuring a large ring with employee numbers around the circumference, enabling workers to print their start and end times on a sheet inside the machine manually.
 3. The Rochester Recorder (1894), invented by Daniel M. Cooper, introduced the world's first card-based system for recording attendance, facilitating more efficient tracking of employees' working hours.

 These innovations helped businesses improve the accuracy and efficiency of their timekeeping and payroll systems, allowing them to grow and thrive.

 Q> Detail the reasons behind IBM's decision to sell its Time Equipment Division to the Simplex Time Recorder Company in the 1950s.
 I> 
 A> In the 1950s, IBM decided to sell its Time Equipment Division to the Simplex Time Recorder Company for several reasons. Most notably, IBM's business had evolved considerably toward data processing, making time equipment products less compatible with the operations of its larger divisions. The company's management, after careful analysis, concluded that focusing on principal product lines best served the interests of IBM, its employees, stockholders, and customers.


 39% 39/100 [03:51<06:14,  6.14s/it]INFO 2024-06-26 20:43:20,845 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Identify the key challenge addressed by the International Time Recording Company (ITR) in its early years.
 I> 
 A> The International Time Recording Company (ITR) primarily addressed the challenge of accurately measuring and expressing the passage of time for businesses to improve payroll processing. In the early 20th century, this was a daunting task for many companies, as manual methods led to inaccuracies and disputes. Seeking a solution, the Bundy Manufacturing Company, ITR's progenitor, developed and introduced the Bundy Key Recorder, which largely eliminated these issues by printing the exact time and an employee's number on a paper tape upon insertion of a specially designed key.

 Q> What were the primary drivers for IBM's shift away from time equipment manufacturing during the 1950s?
 I> 
 A> During the 1950s, IBM's shift away from time equipment manufacturing can be attributed to several primary drivers:

 1. Data processing: As IBM's business evolved dramatically towards data processing, the time equipment manufacturing products, like those of the Time Equipment Division, became increasingly incompatible with the company's primary product lines.

 2. Resource allocation: IBM management decided to devote all their efforts to their principal product lines to better serve the interests of the company, its employees, stockholders, and customers.

 3. Compatibility: The time equipment manufacturing products were identified as less compatible with the operations of the larger divisions within IBM, prompting the decision to sell the Time Equipment Division to the Simplex Time Recorder Company in 1958.


 41% 41/100 [04:03<05:57,  6.06s/it]INFO 2024-06-26 20:43:32,588 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Describe the operation and advantages of the Dial Recorder introduced in 1888 by Alexander Dey.
 I> 
 A> Alexander Dey's Dial Recorder, invented in 1888, was an innovative time recording machine that facilitated accurate payroll processing. Employees would pivot a pointer arm to their individual number on a large ring and press it into a guide hole at the start and end of their shift. The machine would then print the time on a sheet inside, eliminating inaccuracies and disputes. This convenient system allowed for employee identification and time tracking in a straightforward manner.

 Q> What entities merged in 1911 to form the Computing-Tabulating-Recording Company, which was later renamed International Business Machines (IBM)?
 I> 
 A> The Computing-Tabulating-Recording Company was established in 1911 when the Bundy Manufacturing Company, the distributing and controlling company for the International Time Recording Company (ITR), merged with two other firms: the Computing Scale Company of America and the Tabulating Machine Company. Later on, this consolidated entity adopted the renowned name International Business Machines (IBM), as it expanded and diversified its product lines over the years.


 43% 43/100 [04:14<05:36,  5.91s/it]INFO 2024-06-26 20:43:43,682 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Identify how Thomas Watson, as a visionary leader, contributed to IBM's growth and its emphasis on core values.
 I> 
 A> Thomas Watson, as IBM's president from 1914 to 1956, transformed C-T-R (the Computing-Tabulating-Recording Company) into the leading company in the evolution of information technology. Renamed IBM in 1924, Watson guided IBM's expansion into the tabulating machine business, anticipating the impending demand for information technology. Under his leadership, IBM's revenue doubled within four years and internationalized its operation. Furthermore, Watson instilled key corporate values, such as [globalism](<https://www.ibm.com/history/international->

 a>

 > scope), [equal pay for equal work](<https://www.ibm.com/history/diversity->

 a>

 > policies), and an imperative to always [think](<https://www.ibm.com/history/think>). These guiding principles remain integral components of IBM's corporate vision.

 Q> How did a 1914 lawsuit against Thomas Watson and other managers impact the timeline of Watson's full reign at C-T-R? Explain.
 I> 
 A> A legal challenge acted as an unexpected obstacle in Thomas Watson's rise to the presidency of C-T-R. In 1914, Watson and several other NCR executives, including fellow managers, faced a lawsuit under the Sherman Antitrust Act. These allegations necessitated a delay in Watson's complete control over the company. But once the lawsuit was dropped and Watson's name was cleared, he was subsequently promoted to the role of president in the same year. This development set him on a path to reshape C-T-R – a precursor to IBM's legacy – into the dominant force of information technology to come.


 45% 45/100 [04:27<05:32,  6.05s/it]INFO 2024-06-26 20:43:56,476 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> What strategies did Thomas J. Watson employ in revolutionizing C-T-R's focus and culture, ultimately changing the course of the company's development?
 I> 
 A> Thomas J. Watson focused C-T-R's resources on the tabulating machine, recognizing the upcoming demand for information technology, while de-emphasizing the scale and time clock. By creating a strong company culture, he prioritized a unified vision for the company that later became IBM. Watson's emphasis on the tabulating machine and altering the company culture enabled C-T-R to double its revenue within four years. His commitment to equal pay for equal work and an international perspective set the stage for IBM's growth into the powerhouse it is today.

 Q> Identify the process involved in renaming Computing-Tabulating-Recording Company to the more expansive title of International Business Machines.
 I> 
 A> Thomas J. Watson, as the president of Computing-Tabulating-Recording (C-T-R) after a successful lawsuit relieved him of legal constraints, was responsible for renaming the company. The name change was initiated in 1924, and C-T-R became International Business Machines (IBM). This shift acknowledged the expanding scope and ambition of the corporation, which underwent rapid growth and international development after Watson took over as president.


 47% 47/100 [04:38<05:14,  5.94s/it]INFO 2024-06-26 20:44:07,821 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Explain how Herman Hollerith was inspired by earlier technologies and historical figures to create the punched card tabulator.
 I> 
 A> Herman Hollerith's invention of the punched card tabulator was inspired by several historical figures and earlier technologies, such as Joseph Marie Jacquard's use of punched cards in steam-powered weaving looms and Charles Babbage's plans for a computing engine that used instructions from punched cards. Hollerith adapted and refined these concepts for data processing, paving the way for the development of computers and the binary system of zeros and ones used in information processing today.

 Q> Describe the mechanical process of how data was recorded and processed with the punched card tabulator.
 I> 
 A> In the mechanical process of data recording and processing with the punched card tabulator, information was first manually transferred from paper schedules to punched cards using a hole puncher. Once the punched cards were created, they were fed into a card reader that resembled a modern sandwich press. The machine's metal pins connected with a mercury reservoir and closed an electrical circuit when they passed through open holes, registering a "1" on a dial and logging a "0" when there was no connection. This binary principle is still used in detecting the presence or absence of an electrical charge in semiconductors today.


 49% 49/100 [04:49<04:57,  5.84s/it]INFO 2024-06-26 20:44:19,009 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Describe the chief inventions of the International Time Recording Company and their importance in payroll processing.
 I> 
 A> The International Time Recording Company's chief inventions included the Bundy Key Recorder (1888), the Dial Recorder (1888), and the Rochester Recorder (1894). These devices revolutionized payroll processing by accurately recording attendance, eliminating inaccuracies, and reducing disputes in the workplace. The Bundy Key Recorder printed the exact time and an employee's number on a paper tape, while the Dial Recorder featured employee numbers around a large ring with a pointer arm for printing the time. The Rochester Recorder was the world's first card-based system to record attendance, using a printed card with equal spaces representing the days of the week.

 Q> Justify Thomas Watson Jr.'s decision to sell the Time Equipment Division to the Simplex Time Recorder Company in the 1950s based on the company's business transformation.
 I> 
 A> Thomas Watson Jr.'s decision to sell the Time Equipment Division was rooted in the company's transformation from a time equipment manufacturing business to a data processing powerhouse. By the late 1950s, the time equipment products had become less compatible with the operations of IBM's larger divisions. Watson foresaw the need to dedicate all efforts to the data processing and electric typewriter businesses, believing that focusing on the company's stronger divisions would serve the best interests of IBM, its employees, stockholders, and customers.


 51% 51/100 [05:01<04:43,  5.79s/it]INFO 2024-06-26 20:44:30,413 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> What labor-intensive manual process did Herman Hollerith initially aim to automate, which inspired the development of the punched card tabulator?
 I> 
 A> Herman Hollerith initially aimed to automate the labor-intensive manual process of counting questionnaires for the US Census Office. This tedious, error-prone labor of hand-counting the population in a growing country inspired the development of the punched card tabulator, the revolutionary machine that would lay the foundation for modern data processing and computers.

 Q> What propelled the international success of the punched card tabulator, leading countries around the world to adopt it for their own national counts and businesses to employ it for statistical and accounting purposes?
 I> 
 A> The punched card tabulator's success can be attributed to its significant improvements to the data processing workflow compared to manual solutions. The tabulator's exceptional performance in the 1890 US census competition demonstrated its speed and efficiency, which ultimately led to its international adoption. Its successful implementation in the US Census, with a time of 72.5 hours, compared to 144.5 and 100.5 hours for the competitors, made it a go-to solution for countries and businesses seeking accurate and efficient data processing.


 53% 53/100 [05:12<04:30,  5.75s/it]INFO 2024-06-26 20:44:41,678 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Who was Charles Ranlett Flint and what was his role in IBM's history?
 I> 
 A> Charles Ranlett Flint was a financier and businessman who orchestrated the merger of several data-processing technologies, including the Hollerith Tabulating Machine Company, eventually leading to the formation of IBM. He was known as 'Father of Trusts' due to his expertise in merging companies in various industries.

 Q> Describe the difficulties encountered by C-T-R after its founding and how Thomas J. Watson became involved.
 I> 
 A> C-T-R faced significant challenges after being founded, including a stalled business and substantial debt, resistance to integration from some of the original managers, and unclear direction. In response to these difficulties, Charles Ranlett Flint identified the need for a unifying force, which led to the involvement of Thomas J. Watson as IBM's CEO and the subsequent transformation of the company into a global leader in technology, management, and culture.


 55% 55/100 [05:22<04:11,  5.59s/it]INFO 2024-06-26 20:44:52,142 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Who was Charles Ranlett Flint and what sparked his interest in information technologies leading to the creation of C-T-R?
 I> 
 A> Charles Ranlett Flint was a financier and businessman, also known as the 'Father of Trusts,' who had successfully merged companies in various industries, including rubber and wool. In the early 1900s, he shifted his focus to information technologies, showing particular interest in time clocks, computing scales, and the tabulating machine. Recognizing the potential in these data-oriented tools, Flint proposed a merger between three companies with a shared emphasis on data processing, leading to the establishment of C-T-R (Computing-Tabulating-Recording Company) in 1911.

 Q> Describe the situation of C-T-R a few years after its formation and how Thomas J. Watson addressed the company's challenges.
 I> 
 A> A few years after C-T-R's formation, the company faced significant debt and a lack of unity among managers from the merged companies. In response, Charles Ranlett Flint recognized the need for a unifying and charismatic leader, and Thomas J. Watson was appointed as the CEO in 1914. Watson transformed C-T-R into a global force in technology, management, and culture during his 42-year tenure, shaping IBM as we know it today.


 57% 57/100 [05:34<04:04,  5.68s/it]INFO 2024-06-26 20:45:03,888 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Compare and contrast the Jacquard loom's use of punched cards with Herman Hollerith's application of punched cards for census data processing.
 I> 
 A> Joseph Marie Jacquard's Jacquard loom and Herman Hollerith's data processing system both utilized punched cards, albeit with distinct purposes and functionalities. The Jacquard loom, introduced in the early 19th century, applied punched cards to automate the weaving of intricate patterns on steam-powered looms. Over half a century later, Hollerith employed punched cards as a means to store and process demographic data collected during the US census. While the Jacquard loom's punched cards controlled loom operations, Hollerith's system used the cards to record and categorize the data collected, ultimately paving the way for mechanical data processing and the beginnings of computers.

 Q> Summarize the challenges Herman Hollerith faced during the 1890 US census data processing, and the key factors leading to his success.
 I> 
 A> In the 1890 US census, Herman Hollerith encountered various challenges during the data processing phase, including the need to transfer census data manually from paper schedules to punched cards using a hole puncher and feeding the punched cards into a card reader. Despite these obstacles, Hollerith's system excelled by logging faster times than his competitors in both capturing and preparing the data for tabulation. Hollerith's success can be attributed to several key factors, such as applying the binary principle of ones and zeros, which is still in use today, and refining Jacquard's earlier concept of utilizing punched cards for automation via the addition of electrical circuits.


 59% 59/100 [05:46<03:58,  5.82s/it]INFO 2024-06-26 20:45:16,224 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Explain Joseph Marie Jacquard's connection to Herman Hollerith's punched card system.
 I> 
 A> Joseph Marie Jacquard, a French inventor, developed a method for using punched cards in steam-powered weaving looms around 80 years before Herman Hollerith's punched card tabulator. This concept of using punched cards to store and transmit information indirectly influenced Hollerith's development. Although the idea of using punched cards for data processing was not original to Hollerith, he was the first to apply the principle specifically to data processing.

 Q> Detail the two-step process of capturing and preparing data for Hollerith's punched card tabulator system.
 I> 
 A> For Hollerith's punched card tabulator system, the two-step process involved capturing data and preparing it for tabulation. First, census clerks manually transferred census data from paper schedules to punched cards using a hole puncher, allocating a hole for each piece of demographic data collected from surveyed households. The clerks worked at a rate of approximately 500 cards per day. These punched cards were then fed manually into a card reader, which resembled a modern sandwich press. When a pin passed through an open hole in the punched card, it would connect with a mercury reservoir and close an electrical circuit, registering a "1" on the corresponding dial. If no connection was made, it registered a "0." This binary principle of ones and zeros is still employed today in detecting the presence or absence of an electrical charge in semiconductors.


 61% 61/100 [05:58<03:49,  5.87s/it]INFO 2024-06-26 20:45:28,205 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Explain Watson's role in the transformation of the Computing-Tabulating-Recording Company (C-T-R) to become IBM and its implications for the technology industry.
 I> 
 A> Thomas J. Watson took charge of C-T-R in 1914 and led its transformation into IBM by 1924. In his vision, Watson crafted a unified company with a strong culture centered around the tabulating machine, consequently de-emphasizing other products such as time clocks and scales. With doubled revenue in four years, the company expanded its operations across the globe and, in 1924, adopted the new moniker of International Business Machines. Under Watson's influential leadership, IBM rose to prominence as the preeminent player in every evolutionary stage of information technology, setting standards and developing philosophies that persist within the company today.

 Q> Enumerate the philosophies and worldviews IBM developed that distinguish the company from its competitors.
 I> 
 A> IBM is renowned for establishing several core philosophies and worldviews that set it apart from its competitors. Among these are:
 1. Globalism: IBM has consistently held a worldview that values global interconnectedness, collaboration, and diversity.
 2. Equal Pay for Equal Work: IBM pioneered equal pay for equal work decades ago, ensuring that people who share the same responsibilities receive the same compensation.
 3. The Imperative to Always 'Think': Iconic IBM marketing campaigns inspired by Watson's phrase, 'THINK,' have instilled a culture of curiosity, creativity, and innovation within the company.


 63% 63/100 [06:10<03:38,  5.92s/it]INFO 2024-06-26 20:45:40,247 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> What steps did Watson take after becoming president of C-T-R that contributed to the company's growth and renaming to IBM?
 I> 
 A> Upon becoming president of C-T-R following the dismissal of a lawsuit, Thomas J. Watson initiated a campaign of change. He envisioned a unified company and directed resources to the tabulating machine, de-emphasizing other products. This strategic shift more than doubled C-T-R's revenue in four years. With growing international operations, Watson changed the company's name to IBM in 1924, further emphasizing its expanding, global reach.

 Q> Discuss how Watson's early career experiences influenced his leadership at IBM and its growth during his tenure.
 I> 
 A> Watson's earlier career experiences influenced his leadership at IBM in several ways. A born salesman with no formal education, he talked his way into a role with the National Cash Register and rapidly progressed to branch manager. This foundation allowed him to develop strong sales and people skills. Upon joining C-T-R in 1914, Watson utilized his visionary qualities to identify the potential in the tabulating machine, driving IBM's growth through strategic focus and de-emphasizing less promising products. With his charisma and leadership abilities, Watson established philosophies and worldviews that remain central to IBM, such as globalism and equal pay for equal work.


 65% 65/100 [06:22<03:25,  5.87s/it]INFO 2024-06-26 20:45:51,763 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Identify the challenges faced by the Computing-Tabulating-Recording Company (C-T-R) after its inception and how Thomas J. Watson addressed these complications.
 I> 
 A> After the formation of C-T-R, the company faced several challenges, including significant debt and resistance from some managers of the three previous companies that had merged. To surmount these obstacles, Thomas J. Watson recognized that a charismatic leader was needed to unify the organization and propel it forward. Watson's transformative leadership style revitalized the company by fostering full integration, cooperation, and a shared vision among the management teams, enabling C-T-R to eventually evolve into the global powerhouse IBM.

 Q> Explain how Herman Hollerith's tabulating machine expanded beyond census usage to serve various industries.
 I> 
 A> Herman Hollerith's tabulating machine, initially designed to simplify data management for the US Census Bureau, soon found its way into multiple industries beyond census usage. early adopters included the freight office of the New York Central Railroad and the Eastman Kodak Company. These businesses recognized the potential of the tabulator's hole-punch technology in managing product, train traffic, and insurance customer information. Applying the tabulator's hole-punch system to industry-specific data allowed companies to streamline operations, improve efficiency, and optimize decision-making, paving the way for technology-driven innovation across various sectors.


 67% 67/100 [06:33<03:11,  5.82s/it]INFO 2024-06-26 20:46:03,151 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Who was the inventor of the tabulating machine, and what significant event established the machine's credibility and success?
 I> 
 A> The tabulating machine was invented by Herman Hollerith, a young engineer and former census clerk. Its credibility and success were established when it was first adopted by the US Census Bureau in the late 1800s. The tabulator's hole-punch system significantly sped up the data collection and analysis process, reportedly saving the US government two years and USD 5 million during the 1890 census. As a result, census agencies around the world quickly incorporated the technology into their operations, while businesses discovered its numerous applications in tracking and managing products, train traffic, and insurance customers.

 Q> Discuss the primary reasons for C-T-R's poor business performance in the years following the merger.
 I> 
 A> Following the merger that led to the formation of C-T-R in 1911, the company experienced some business challenges and underperformance. One of the reasons was a significant amount of debt carried on the balance sheet. Additionally, resistance to full integration persisted among the managers from the three previous companies. This resentment and reluctance led to a fragmented operation, causing inefficiencies and strategic misalignment that hindered the company's overall performance.


 69% 69/100 [06:45<03:00,  5.81s/it]INFO 2024-06-26 20:46:14,725 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Explain how Herman Hollerith's childhood experiences in his father's mill influenced the development of his punched card tabulator.
 I> 
 A> Herman Hollerith's early experiences working in his father's mill, where mechanical systems were employed to process and categorize lumber, greatly influenced his later invention of the punched card tabulator. The mill utilized various mechanical levers, gears, and belts, which Hollerith would later adapt in the form of the punched cards, levers, and electrical circuits to process census data.

 Furthermore, watching his father employ mechanical strategies in the mill inspired Hollerith to seek a more efficient method of data processing for the US Census, as he understood that manual labor and hand-counting were prone to human error and inefficiency. By drawing upon his background with mechanical systems, Hollerith successfully applied the foundation of his father's millwork principles to his punched card tabulator technology.

 Q> Outline the key accomplishments of Herman Hollerith and the role they played in shaping the field of data processing.
 I> 
 A> Herman Hollerith's achievements in the field of data processing remain seminal to this day:

 1. **Automating the census process**: Hollerith's invention of the punched card tabulator revolutionized the census-taking process in the US by automating manual data counting, thereby reducing time, effort, and human error.

 2. **Establishing punched card technology**: Hollerith's machinery introduced punched cards as a means to mechanically read and record data, opening up endless possibilities for data processing and handling.

 3. **Sparking IBM's growth**: Hollerith's inventions laid the groundwork for the formation of the IBM Corporation—then Computing-Tabulating-Recording Company—and its dominance in the data processing and computing industries through the next few decades.

 4. **Inspiring computer development**: Hollerith's tabulating machines, based on punched card and binary principles, contributed substantially to the development of modern computer systems.

 5. **International adoption**: Following the success in the US census, the tabulating system was licensed and adopted by multiple countries for their own census operations, further proliferating the technology and its influence.


 71% 71/100 [06:59<02:58,  6.15s/it]INFO 2024-06-26 20:46:28,619 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Identify the three separate firms that were brought together under C-T-R's management in 1911 and list the locations of their factories.
 I> 
 A> C-T-R merged three separate firms in 1911: the International Time Recording Company, the Computing Scale Company, and the Tabulating Machine Company. These firms were based in different cities, with factories operating in Dayton, Ohio, Detroit, Michigan, and Toronto, Canada in addition to the headquarters in Endicott, New York.

 Q> Describe Charles Flint's activities before investing in information technologies and his subsequent vision for these tools.
 I> 
 A> Before investing in information technologies, Charles Flint was a financier and businessman known for bundling companies in rubber and wool industries. He earned the nickname "Father of Trusts." Flint shifted his interests to information technology after observing a wide range of industries around the turn of the century. He had particular interests in the time clock, computing scale, and tabulating machine, which were mechanical and computational tools that shared a common emphasis on data. Flint envisioned these tools collectively providing a great deal of value in industry and facilitated the merger of three companies to form C-T-R as a holding company in 1911.


 73% 73/100 [07:10<02:41,  5.99s/it]INFO 2024-06-26 20:46:39,860 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Who was the inventor that first applied punched cards to data processing, and when was the tabulating machine used extensively in national censuses?
 I> 
 A> Herman Hollerith was the pioneering inventor who first applied punched cards to data processing in the 1880s. Extensive international use of his tabulating machine in national censuses began shortly after its successful deployment in the 1890 US census. Countries like Austria, Canada, Cuba, France, Norway, the Philippines, and Russia procured Hollerith's tabulator for their own national censuses.

 Q> Explain how Herman Hollerith's binaries principle is still used in the present day, and in what machine was this principle first employed.
 I> 
 A> Herman Hollerith's binary principle is the foundation of modern electronics, including modern semiconductors. In his punched-card system, the presence or absence of a punched hole represented a "1" or "0." The same concept lies at the core of today's digital devices, where electrical charges detect the presence or absence of electrons, or "1" and "0" accordingly. This binary system was first employed in the card reader, which resembled a modern sandwich press, featuring spring-loaded metal pins to connect with mercury reservoirs and close electrical circuits, generating pulses that registered demographic data.


 75% 75/100 [07:22<02:28,  5.95s/it]INFO 2024-06-26 20:46:51,567 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Who was the primary competitor of Hollerith's tabulator during the competition held by the Census Office for the 1890 census?
 I> 
 A> During the competition held by the Census Office for the 1890 census, Hollerith's primary competitor was a machine that clocked in at 100.5 hours to capture the data used for the challenge.

 Q> What were the main functions of the machines and gadgets in Hollerith's multistage tabulating process?
 I> 
 A> The main functions of Hollerith's machines and gadgets in the multistage tabulating process involved recording, sorting, and compiling the census information. Clerks would manually transfer census data from paper schedules to punched cards using a hole puncher. The punched cards were then fed into a card reader, which would resemble a modern sandwich press and connect with a mercury reservoir to register a '1' or '0' on 40 dials based on the holes in the cards. A separate machine would sort the cards into as many as 24 categories based on the location of the holes.


 77% 77/100 [07:33<02:14,  5.85s/it]INFO 2024-06-26 20:47:02,809 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Elaborate on Thomas J. Watson's promotion and the role he played in the transformation of C-T-R to IBM.
 I> 
 A> Thomas J. Watson, previously general manager of C-T-R, was promoted to president in 1915 after his name was cleared in a legal case. He took charge of the company with approximately 1,300 employees and set out to implement a major transformation. Watson demonstrated visionary foresight by identifying the demand for tabulating machines and strategically shifting resources to prioritize their development. He de-emphasized other products, such as scales and time clocks, which was an essential step in fostering a unified company culture. As a result of Watson's focus and leadership, revenue at C-T-R doubled within four years. In 1924, he led the expansion of the company's operations internationally and changed the name to International Business Machines (IBM), marking a significant milestone in the organization's growth and recognition as a leading player in the information technology industry.

 Q> What philosophies and worldviews did IBM adopt during Thomas J. Watson's tenure, and how do these continue to impact the company today?
 I> 
 A> During Thomas J. Watson's leadership, IBM adopted several philosophies and worldviews that have left a lasting impact on the company, including globalism, equal pay for equal work, and the imperative to think. IBM's commitment to globalism has led to its expansion into various international markets and cultivation of a global workforce. The company has long advocated for gender and racial equality by continuously promoting diversity and equal pay for equal work. Moreover, the "Think" motto remains a cornerstone of the company's values and is still reflected in IBM's innovative and forward-thinking approach to the evolution of information technology.


 79% 79/100 [07:45<02:05,  5.95s/it]INFO 2024-06-26 20:47:15,202 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Explicate the philosophies and worldviews espoused by Thomas J. Watson and IBM during Watson's leadership.
 I> 
 A> Under the direction of Thomas J. Watson, IBM embraced three core philosophies: [globalism](https://www.ibm.com/history/international-scope), [equal pay for equal work](https://www.ibm.com/history/diversity-policies), and the imperative to always [think](https://www.ibm.com/history/think). As a globalist, Watson fostered IBM's expansion into international markets, resulting in a subsequent shift in C-T-R's moniker to International Business Machines. IBM, under Watson's leadership, also became a pioneer in implementing equal pay for equal work, remaining committed to ensuring gender pay equality in the company's workforce. The "Think" campaign, initiated by Watson, urged employees to embrace innovative solutions and creative thinking, shaping IBM's longstanding, forward-thinking corporate culture.

 Q> Trace the origins of IBM's core values and the origins of the company name, International Business Machines (IBM).
 I> 
 A> IBM, originally known as C-T-R, changed its name to International Business Machines (IBM) in 1924 after experiencing rapid growth and expansion under Thomas J. Watson's leadership. Before his time at C-T-R, Watson was an employee at National Cash Register and rose to the position of branch manager. Watson's appreciation for international scope emerged while working for NCR, where he identified the need and envisioned a company specializing in information technology on a global level. This vision prompted the transition from C-T-R to IBM. Among IBM's core values are [globalism](https://www.ibm.com/history/international-scope), [equal pay for equal work](https://www.ibm.com/history/diversity-policies), and the imperative to always [think](https://www.ibm.com/history/think), philosophies instilled by Watson and remaining integral to IBM's mission and culture.


 81% 81/100 [07:59<01:57,  6.17s/it]INFO 2024-06-26 20:47:28,531 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Explain how Thomas J. Watson, while at IBM, shifted the company's focus to the tabulating machine and its impact on revenue.
 I> 
 A> Under Thomas J. Watson's leadership at IBM, the company strategically shifted its focus towards the tabulating machine, recognizing the growth of information technology. This strategic shift led to tremendous success, as C-T-R's revenue doubled within four years. With a more expansive vision, Watson expanded IBM's operations internationally and renamed the company to its current name in 1924. This created a strong foundation for IBM, cementing its role as a global leader in evolving information technology.

 Q> Identify and outline IBM's core philosophies and worldviews that emerged during Watson's tenure and explain their significance to the company's growth and development.
 I> 
 A> IBM, under the leadership of Thomas J. Watson, developed several core philosophies and worldviews that are still integral to the company. First, [globalism](https://www.ibm.com/history/international-scope) focused on expanding overseas, which contributed to IBM's growth and presence in international markets. Second, [equal pay for equal work](https://www.ibm.com/history/diversity-policies) promoted gender equality and inclusivity, enhancing employee satisfaction and productivity. Finally, the [Think](https://www.ibm.com/history/think) doctrine encouraged problem-solving and innovation, making IBM a resilient and adaptive global enterprise.


 83% 83/100 [08:10<01:43,  6.08s/it]INFO 2024-06-26 20:47:40,255 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> List the major improvements that Thomas J. Watson brought to C-T-R during his tenure as CEO.
 I> 
 A> During his tenure as CEO, Thomas J. Watson brought a number of major improvements to C-T-R, contributing to its transformation into IBM:
 1. Implementing an aggressive, centralized sales management strategy
 2. Introducing strict business ethics standards, fostering a positive corporate culture
 3. Diversifying the product line for unit record equipment
 4. Establishing global manufacturing and sales operations, positioning the company as an international leader
 5. Implementing a comprehensive internal training and education program for employees
 6. Relaunching the brand under the name International Business Machines (IBM)

 These changes elevated IBM to a competitive and respected international company in the world of technology and emphasized the importance of ethical corporate practices.

 Q> Outline the origins of the tabulating machine and the punch-card system, and name those who influenced Herman Hollerith during their development.
 I> 
 A> The tabulating machine and punch-card system can be traced back to Joseph Marie Jacquard, who first introduced punched cards in the early 1800s as a way to automate steam-powered weaving looms. Charles Babbage later envisioned a computing engine, known as the Analytical Engine, which would perform arithmetic calculations using instructions from punched cards in the 1830s.

 Herman Hollerith was undoubtedly influenced by these pioneers, leading him to invent the punched card tabulator during the 1880s. His invention built upon Jacquard's punched cards and Babbage's concept of arithmetic calculations with instructions from punched cards while adapting the technology to the field of data processing.


 85% 85/100 [08:23<01:32,  6.15s/it]INFO 2024-06-26 20:47:52,924 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> What strategies did Thomas J. Watson implement to drive growth at IBM?
 I> 
 A> Under Thomas J. Watson's leadership, IBM adopted several growth strategies. He focused resources on the tabulating machine to meet the expected demand for information technology, de-emphasizing the scale and time clock. Additionally, he expanded operations internationally, culminating in the 1924 name change to International Business Machines.

 Q> Analyze the factors that contributed to Thomas J. Watson becoming the president of Computing-Tabulating-Recording Company.
 I> 
 A> Thomas J. Watson's journey to becoming the president of Computing-Tabulating-Recording Company involved several contributing factors. Previously, as a branch manager at National Cash Register, he proved to be a successful salesman and manager, quickly rising through the ranks. Flint then hired him as general manager of C-T-R. After a legal conflict delayed his promotion, the dropping of the lawsuit allowed him to assume the role of president in 1914. His past achievements and leadership potential culminated in his appointment as president of C-T-R.


 87% 87/100 [08:34<01:17,  5.95s/it]INFO 2024-06-26 20:48:03,854 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> What were the main reasons for the Time Equipment Division's decreased compatibility with IBM's core businesses, and why did Thomas Watson Jr. decide to sell it?
 I> 
 A> In the 1950s, IBM's focus had shifted dramatically toward data processing, which made the Time Equipment Division's products increasingly less compatible with the operations of IBM's larger divisions. IBM's management concluded that the best interests of the company, its employees, stockholders, and customers could be served by dedicating all efforts to the principal product lines.

 As a result, Thomas Watson Jr. decided to sell the Time Equipment Division to the Simplex Time Recorder Company in 1958. This decision allowed IBM to concentrate on its core businesses, ultimately leading to the optimization of the company's resources, talents, and competencies.

 Q> How did the merging of the International Time Recording Company, the Computing-Tabulating-Recording Company, and other firms in 1911 eventually lead to the formation of IBM?
 I> 
 A> After the merger between the International Time Recording Company, the Computing-Tabulating-Recording Company, and other firms in 1911, the newly-formed company operated under the name Computing-Tabulating-Recording Company. This merger brought together various organizations focusing on different items such as time recorders, punched-card equipment, and tabulating machines. Over time, recognizing the potential for growth and innovation beyond its original product lines, the company underwent a name change, transforming into International Business Machines (IBM).


 89% 89/100 [08:46<01:06,  6.00s/it]INFO 2024-06-26 20:48:16,124 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Identify the reasons why Thomas J. Watson improved the culture and focus of C-T-R, leading eventually to the creation of IBM.
 I> 
 A> Thomas J. Watson improved the culture and focus of C-T-R for various reasons: (1) by envisioning and crafting a unified company with a strong and engaging work environment, (2) concentrating resources on the tabulating machine, which he recognized had significant latent demand as an early information technology, and (3) downplaying the less promising scale and time clock products. These strategic actions contributed to C-T-R's revenue doubling within four years. Following the expansion of foreign operations, Watson renamed C-T-R as International Business Machines (IBM) in 1924, marking the foundation of the company we know today.

 Q> What changes did IBM implement in its initial years that allowed it to secure its current position as the leading company in information technology?
 I> 
 A> IBM's initial years were marked by a number of transformative changes. After Thomas J. Watson took charge as general manager in 1914, he sensed the impending demand for tabulating machines—a type of information technology—and reallocated C-T-R's resources accordingly, de-emphasizing scales and time clocks. With his help, the company expanded internationally and thrived under his leadership as president. IBM's commitment to innovation and strong corporate culture laid the groundwork for a lasting impact on the industry.


 91% 91/100 [08:58<00:53,  5.97s/it]INFO 2024-06-26 20:48:27,939 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Describe one of IBM's progenitors, the International Time Recording Company (ITR), and its role in revolutionizing payroll processing.
 I> 
 A> The International Time Recording Company (ITR) was a crucial IBM progenitor that significantly impacted payroll processing. Founded in 1900, ITR emerged from the Bundy Manufacturing Company's time recording business following George W. Fairchild's request. ITR's primary objective was to address the widespread challenge businesses faced in accurately measuring and expressing the passage of time. Its revolutionary inventions, such as the Bundy Key Recorder and the Rochester Recorder, greatly reduced inaccuracies and disputes in payroll processing, making it a critical pioneer in automated timekeeping solutions.

 Q> Discuss the preceding companies to IBM and their inventions, which led to the formation of IBM in 1911.
 I> 
 A> Three notable companies preceded the formation of IBM in 1911: the Bundy Manufacturing Company, the International Time Recording Company (ITR), and the Computing-Tabulating-Recording Company. The Bundy Manufacturing Company, founded by Willard Bundy in 1888, created the Bundy Key Recorder, an influential mechanical time recorder. ITR, which was spun out of the Bundy Company and led by George W. Fairchild, facilitated accurate payroll processing with their inventions like the Bristol Clock and the Dey Dial Recorder. The Computing-Tabulating-Recording Company, formed in 1907 as a result of ITR's relocation to Endicott, New York, amalgamated with the Tabulating Machine Company and the Computing Scale Company to eventually become IBM in 1911.


 93% 93/100 [09:11<00:42,  6.09s/it]INFO 2024-06-26 20:48:40,674 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> What changes did Watson implement at C-T-R that allowed the company's revenue to double within four years?
 I> 
 A> Thomas Watson, after taking charge of C-T-R as general manager in 1914, recognized the potential of the tabulating machine and de-emphasized competing product lines such as the scale and time clock. By investing resources into the tabulating technology, Watson positioned C-T-R to capitalize on the surging demand for information management systems, a bet that paid off when the company's revenue doubled within four years.

 Q> What key event in Watson's career at NCR provided a foundation for the principles he implemented at IBM?
 I> 
 A> In Thomas Watson's early career at National Cash Register (NCR), he was involved in a lawsuit for violating the Sherman Antitrust Act. Despite the charges, Watson remained undeterred and continued to excel, eventually rising to branch manager within a few years. This experience perhaps shaped Watson's management style and commitment to ethical practices throughout his career, ultimately laying the groundwork for IBM's core values, including [globalism](<https://www.ibm.com/history/international->

 a>

 > scope), [equal pay for equal work](<https://www.ibm.com/history/diversity->

 a>

 > policies), and an imperative to always [think](<https://www.ibm.com/history/think>).


 95% 95/100 [09:23<00:30,  6.10s/it]INFO 2024-06-26 20:48:52,880 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Explain how and why Charles Ranlett Flint backed the tabulating machine.
 I> 
 A> Charles Ranlett Flint financially backed the tabulating machine due to his belief in the potential of data-processing technologies. He had already established himself as a successful investor in a variety of industries such as rubber and wool, and wanted to expand his horizons by supporting an ambitious merger in an emerging technological sector. After merging the International Time Recording Company, the Computing Scale Company, and the Tabulating Machine Company, Flint envisioned the tabulator's hole-punch system expanding its utility beyond census data to include information gathered on products, train traffic, and insurance customers. He recognized the growing demand for information technology, which made the tabulating machine an attractive and strategic investment.

 Q> Characterize the influence of the US Census Bureau on the dynamics of the tabulating machine industry, as demonstrated by the work of Herman Hollerith.
 I> 
 A> The US Census Bureau had a profound influence on the tabulating machine industry, as it catalyzed Herman Hollerith's development and uncovered the technology's potential. In the late 1800s, Hollerith invented the tabulating machine to assist the US Census Bureau in collecting and processing data efficiently. Building upon earlier hole-punch technologies, his design enabled the Bureau to save two years and USD 5 million during the 1890 census. The widespread adoption of the tabulating machine by various national and international census agencies further solidified its significance, demonstrating its data-handling capabilities and opening the doors for businesses to exploit its potential. The success at the Census Bureau helped grow demand and establish the industry that eventually evolved into IBM.


 97% 97/100 [09:36<00:18,  6.14s/it]INFO 2024-06-26 20:49:05,340 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> Explain the origin and significance of punched cards in the development of the tabulator.
 I> 
 A> Punched cards have a rich history dating back to the early 19th century, when Joseph Marie Jacquard invented a system for automating steam-powered weaving looms using punched cards. Later, Charles Babbage developed plans for a computing engine using punched cards. Herman Hollerith was the first to apply this concept to data processing, creating punched cards as a storage and input medium for his 1880s tabulator. This innovation revolutionized data processing and paved the way for the development of more advanced computing technologies.

 Q> Summarize the achievements and challenges of Herman Hollerith during the creation and testing of the punched card tabulator.
 I> 
 A> Herman Hollerith's journey with the punched card tabulator is marked by achievements and challenges. Among his achievements were a series of innovations; he was the first to apply punched cards to data processing. With his tabulator, he won a crucial competition against two competitors in 1888 by processing census data much faster than his contemporaries. The challenges involved testing the machine, which included adapting the technology from using strips of paper to punched cards, acquiring patents, and improving the overall speed and efficiency of the tabulation process.


 99% 99/100 [09:47<00:06,  6.04s/it]INFO 2024-06-26 20:49:16,945 generate_data.py:505: generate_data Selected taxonomy path knowledge->textbook->history->ibm_history
 Q> What were the primary inventions that led to the success of IBM's Time Equipment Division?
 I> 
 A> The initial success of IBM's Time Equipment Division was driven by three significant inventions. In 1888, the Bundy Key Recorder was introduced, which reduced inaccuracies and disputes in payroll processing by printing the exact time and employee number on a paper tape. The following year, the Dial Recorder was invented by Alexander Dey, which featured a circular layout for employee numbers and used a pointer arm to create time impressions. In 1894, Daniel M. Cooper patented the Rochester Recorder, the world's first card-based system for attendance recording, using printed cards divided into seven spaces for the days of the week.

 Q> Explain how the International Time Recording Company evolved into IBM, including the date and reasons for the transformations.
 I> 
 A> The International Time Recording Company (ITRC) was created in 1900 as a spin-off from the Bundy Manufacturing Company. It was formed to contend with businesses struggling to accurately measure the passage of time for payroll processing. ITR became IBM's precursor. In 1907, ITR moved to Endicott, New York, which many consider IBM's birthplace. In 1911, ITR merged with two other firms and became the Computing-Tabulating-Recording Company (C-T-R). Thomas J. Watson, ITR's former general manager, took over as C-T-R's president in 1915 and transformed the company by focusing on tabulating machines, which significantly improved the company's performance. In 1924, C-T-R expanded internationally and changed its name to International Business Machines (IBM).


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 upload failed: ../outputtopush/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T20_12_38.json to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/knowledge/textbook/history/ibm_history/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T20_12_38.json An error occurred (BadDigest) when calling the PutObject operation: The Content-MD5 you specified did not match what we received.
 compositional_skills/extraction/fda_filing/markdown/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/extraction/fda_filing/markdown/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/fda_filing/markdown --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T20:50:33Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/extraction/fda_filing/markdown/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.
 Error: An example in the taxonomy path compositional_skills->extraction->fda_filing->markdown is too long for the server context size of 4096. Ensure the total number of characters across the combined question, answer, and context is less than 4896 for each example or use a server with a larger context size.
 compositional_skills/extraction/email/reasoning/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/extraction/email/reasoning/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/email/reasoning --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T20:50:43Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/extraction/email/reasoning/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 20:50:52,251 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Who is the individual sending this email to request approval?
 I> Subject: Account Termination Request

 Date:

 Thursday, March 17, 2022 at 1:35:16 PM Central Standard Time

 From:

 David Church

 To:

 Executive Team

 Dear Executive Team,

 I am writing to formally request the termination of the Pro account for client XYZ, account number P-000123. I am the account administrator for this account and I appreciate your consideration of my request.

 Reason for Termination:

 XYZ has consistently failed to meet the acceptable terms of use for our product. This violation of policy has led to misuse of the account, causing negative impacts to our network security and resources.

 Next Steps:

 Please confirm receipt of this request and let me know the expected timeline for processing.

 Thank you for your time and assistance,

 David Church

 Account Administrator
 A> The individual sending this email is David Church. He sent the email to the Executive Team to request the termination of the Pro account for a specific client.


  1% 1/100 [00:06<11:11,  6.78s/it]INFO 2024-06-26 20:50:59,031 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the delivery date for the final monitor in Luke's email?
 I> Subject: High-Def Monitor Update

 Date:

 Friday, February 23, 2024 at 9:13:32$_{ }$PM Eastern Standard Time

 From:

 Luke Inglis

 To:

 Kate Soule

 Hi Kate,

 I am writing to explain to you the delay in our lab receiving monitors. On Dec 2$^{nd,}$ 2023, I started the process of purchasing 7 high-def Samsung monitors for the MIT-IBM Watson AI Lab. I think you already know, but I wanted to outline the steps needed to make this purchase.

 ...

 | Monitor       | Price  | Estimated Arrival  |
 |----------------------|---------|---------------------|
 | Odyssey Ark 55-inch | $1,952 | 5/10/2024      |

 Regards,

 Luke Inglis Operations Manager AI Models & MIT-IBM Watson AI Lab IBM Research
 A> The delivery date for the final monitor in Luke's email is on May 10, 2024.


  2% 2/100 [00:13<11:27,  7.02s/it]INFO 2024-06-26 20:51:06,217 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What was the initial issue that caused the delay in the order?
 I> Subject: High-Def Monitor Update

 Date:

 Friday, February 23, 2024 at 9:13:32$_{ }$PM Eastern Standard Time

 From:

 Luke Inglis

 To:

 Kate Soule

 Hi Kate,

 I am writing to explain to you the delay in our lab receiving monitors. On Dec 2$^{nd,}$ 2023, I started the process of purchasing 7 high-def Samsung monitors for the MIT-IBM Watson AI Lab. I think you already know, but I wanted to outline the steps needed to make this purchase.

 1. Obtain a quote from Samsung

 2. Submit an Expense Pre-Approval

 3. Approval from Line VP

 4. Submit an Ad Hoc request to Procurement

 5. Approval from Manager

 6. Approval from 2$^{nd}$ line Manager

 7. Approval from Finance

 8. Procurement then identifies their specialist for this request

 9. The Procurement specialist then reviews the request and determines which supplier to use and reaches out to the contact person there

 10. These two finalize agreements needed to execute the order

 11. Monitors are then shipped to our location

 We have now finally reached number 11 in this process. Below I wanted to outline what we are receiving and when they are expected to arrive.

 | Monitor       | Price  | Estimated Arrival  |
 |----------------------|---------|---------------------|
 | Odyssey Ark 55-inch | $1,952 | 5/10/2024      |
 | Odyssey G7 32-Inch  | $669  | 3/7/2024      |
 | Odyssey G7 32-Inch  | $669  | 3/7/2024      |
 | Odyssey G55C 27-Inch | $297  | 2/27/2024      |
 | Odyssey G55C 27-Inch | $297  | 2/27/2024      |

 Specifically, I wanted to address the shipping date for the Odyssey Ark 55-inch. I know the 10th of May 2024 is not ideal but there was confusion as the supplier is in Europe and thought that 5/10/2024 was actually 10/5/2024.

 I apologize for the confusion.

 Regards,

 Luke Inglis Operations Manager AI Models & MIT-IBM Watson AI Lab IBM Research
 A> The initial issue that caused the delay in the order was that the supplier, who is in Europe, mistook the date 5/10/2024 for 10/5/2024. This misunderstanding caused a delay in the shipping of the Odyssey Ark 55-inch monitor to the MIT-IBM Watson AI Lab.

 Q> What is the estimated delivery date for the 55-inch Samsung Odyssey Ark monitor?
 I> Subject: High-Def Monitor Update

 Date:

 Friday, February 23, 2024 at 9:13:32$_{ }$PM Eastern Standard Time

 From:

 Luke Inglis

 To:

 Kate Soule

 Hi Kate,

 I am writing to explain to you the delay in our lab receiving monitors. On Dec 2$^{nd,}$ 2023, I started the process of purchasing 7 high-def Samsung monitors for the MIT-IBM Watson AI Lab. I think you already know, but I wanted to outline the steps needed to make this purchase.

 1. Obtain a quote from Samsung

 2. Submit an Expense Pre-Approval

 3. Approval from Line VP

 4. Submit an Ad Hoc request to Procurement

 5. Approval from Manager

 6. Approval from 2$^{nd}$ line Manager

 7. Approval from Finance

 8. Procurement then identifies their specialist for this request

 9. The Procurement specialist then reviews the request and determines which supplier to use and reaches out to the contact person there

 10. These two finalize agreements needed to execute the order

 11. Monitors are then shipped to our location

 We have now finally reached number 11 in this process. Below I wanted to outline what we are receiving and when they are expected to arrive.

 | Monitor       | Price  | Estimated Arrival  |
 |----------------------|---------|---------------------|
 | Odyssey Ark 55-inch | $1,952 | 5/10/2024      |
 | Odyssey G7 32-Inch  | $669  | 3/7/2024      |
 | Odyssey G7 32-Inch  | $669  | 3/7/2024      |
 | Odyssey G55C 27-Inch | $297  | 2/27/2024      |
 | Odyssey G55C 27-Inch | $297  | 2/27/2024      |

 Specifically, I wanted to address the shipping date for the Odyssey Ark 55-inch. I know the 10th of May 2024 is not ideal but there was confusion as the supplier is in Europe and thought that 5/10/2024 was actually 10/5/2024.

 I apologize for the confusion.

 Regards,

 Luke Inglis Operations Manager AI Models & MIT-IBM Watson AI Lab IBM Research
 A> The estimated delivery date for the 55-inch Samsung Odyssey Ark monitor is May 10, 2024.


  4% 4/100 [00:38<16:23, 10.24s/it]INFO 2024-06-26 20:51:30,539 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Extract the salutation (greeting) from the email to determine how the sender is addressing the recipient.
 I> Subject: High-Def Monitor Update

 Date:

 Friday, February 23, 2024 at 9:13:32$_{ }$PM Eastern Standard Time

 From:

 Luke Inglis

 To:

 Kate Soule

 Hi Kate,

 I am writing to explain to you the delay in our lab receiving monitors.

 ...

 Regards,

 Luke Inglis

 Operations Manager AI Models & MIT-IBM Watson AI Lab IBM Research
 A> The salutation from the email is "Hi Kate," which shows that the sender is addressing the recipient by her first name.


  5% 5/100 [00:44<14:10,  8.96s/it]INFO 2024-06-26 20:51:36,625 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Identify the issue that the email is discussing and describe it in detail.
 I> Subject: High-Def Monitor Update

 Date:

 Friday, February 23, 2024 at 9:13:32$_{ }$PM Eastern Standard Time

 From:

 Luke Inglis

 To:

 Kate Soule

 Hi Kate,

 I am writing to explain to you the delay in our lab receiving monitors. On Dec 2$^{nd,}$ 2023, I started the process of purchasing 7 high-def Samsung monitors for the MIT-IBM Watson AI Lab. We have now finally reached number 11 in this process, which is the point at which the monitors are shipped to our location. However, there has been confusion regarding the delivery date for the Odyssey Ark 55-inch monitor. The supplier is located in Europe and thought that 5/10/2024 was actually 10/5/2024. As a result, the monitor is not expected to arrive until May 10, 2024, which is later than expected.

 Regards,

 Luke Inglis

 Operations Manager AI Models & MIT-IBM Watson AI Lab IBM Research
 A> The issue discussed in the email is a delay in the delivery of a high-def Samsung monitor to the MIT-IBM Watson AI Lab. The delay is due to confusion regarding the delivery date for the Odyssey Ark 55-inch monitor. The supplier is located in Europe and thought that 5/10/2024 was actually 10/5/2024, resulting in a later than expected delivery date of May 10, 2024.

 Q> Locate the specific monitors that will be delivered on March 7, 2024.
 I> Subject: High-Def Monitor Update

 Date:

 Friday, February 23, 2024 at 9:13:32$_{ }$PM Eastern Standard Time

 From:

 Luke Inglis

 To:

 Kate Soule

 Hi Kate,

 I am writing to explain to you the delay in our lab receiving monitors.

 ...

 | Monitor       | Price  | Estimated Arrival  |
 |----------------------|---------|---------------------|
 | Odyssey Ark 55-inch | $1,952 | 5/10/2024      |
 | Odyssey G7 32-Inch  | $669  | 3/7/2024      |
 | Odyssey G7 32-Inch  | $669  | 3/7/2024      |
 | Odyssey G55C 27-Inch | $297  | 2/27/2024      |

 ...

 Regards,

 Luke Inglis

 Operations Manager AI Models & MIT-IBM Watson AI Lab IBM Research
 A> The specific monitors that will be delivered on March 7, 2024 are the Odyssey G7 32-Inch monitors. There are two of them, and they will be delivered on the same day.


  7% 7/100 [01:00<13:22,  8.63s/it]INFO 2024-06-26 20:51:53,163 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Extract the date when the email was sent and provide it in MM/DD/YYYY format.
 I> Subject: Requirement Gathering Meeting

 Date:

 Monday, May 23, 2022 at 09:23:45 -0500

 To:

 Susan R. Stratton

 From:

 Allan Budzien

 CC:

 Daniel Furtado

 Hello Susan,

 I am writing to suggest a meeting where we can gather all the requirements for this new project. I believe that we have to consider the timeline, project scope, user stories and complete the documentation of these project essentials.

 Would it be possible to schedule this meeting a week from today? If the suggested timing does not suit you, kindly suggest a better day or time; I will then confirm the new meeting details.

 Thank you for your time and attention.

 Best regards,

 Allan
 A> The date when the email was sent is 05/23/2022.

 Q> Identify the requester and the requested action related to the Budget Analysis project.
 I> Subject: Budget Analysis Project Status

 Date:

 December 6, 2022 at 3:30:29 PM EST

 To:

 Taylor Simmons

 From:

 Bethany Duke

 CC:

 <noinput>

 Hi Taylor,

 Please find the revised budget analysis with the new timeline for the Building 5 HVAC project. I have updated the costs to include increased material costs and made the necessary changes in the schedule.

 The project is set to start by January 3, 2023, and complete by June 30, 2023. The updated budget is shown in the "Budget Analysis v3" tab. I would appreciate if you could verify and approve the budget as soon as possible, so we can share this with the other stakeholders.

 Thank you,

 Bethany

 Project Specialist
 A> The requester is Bethany Duke, and she requested that Taylor Simmons verify and approve the revised budget analysis for the Building 5 HVAC project.


  9% 9/100 [01:14<12:03,  7.95s/it]INFO 2024-06-26 20:52:07,037 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 INFO 2024-06-26 20:52:10,787 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Who is the sender of the email, and what is the primary topic of the email?
 I> Subject: Meeting Reminders for the Upcoming Week

 Date:

 Monday, August 1, 2022 at 10:00:00 AM Eastern Standard Time

 To:

 Annie Chen-Law

 From:

 Timothy Monroe

 CC:

 <noinput>

 Hi Annie,

 Please find below the list of meetings for the upcoming week:

 - Monday, August 1: Project Kickoff at 3 pm
 - Tuesday, August 2: Q3 Status Review at 9 am
 - Wednesday, August 3: HR Workshop at 11 am
 - Friday, August 5: R&D downtime 8 am - 12 pm

 Best,

 Timothy Monroe
 Team Lead
 A> The sender of the email is Timothy Monroe, and the primary topic of the email is the list of meeting reminders for the upcoming week.

 Q> Which items are included in the packing list sent by Maria?
 I> Subject: Office Move Checklist

 Date:

 Friday, June 10, 2022 at 12:45:13 PM Eastern Standard Time

 From:

 Maria Rodriguez

 To:

 Aidan Campbell

 CC:

 <noinput>

 Hi Aidan,

 Please find the office move checklist attached. Kindly verify and double-check the list for accuracy, and ensure all items are accounted for.

 - Boxes
 - tapes & markers
 - whiteboard & markers
 - chair & small table
 - computer (monitor, keyboard, mouse, & cables)

 Best,

 Maria Rodriguez
 Team Assistant
 A> The packing list sent by Maria includes boxes, tapes & markers, whiteboard & markers, a chair & small table, and a computer with its respective components (monitor, keyboard, mouse, and cables).


 11% 11/100 [01:31<12:01,  8.11s/it]INFO 2024-06-26 20:52:23,810 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Who is responsible for approving the "IT Asset Disposal" in the provided email?
 I> Subject: IT Asset Disposal

 Date: 

 February 9, 2023 at 10:15:00 AM Pacific Standard Time
 To:

 Jennifer Johnson

 From:

 Terrence Lee

 CC:

 <noinput>

 Hi Jennifer,

 I need your approval for the "IT Asset Disposal" request. We have submitted the disposal to the eWaste vendor today (02/09/23) and have held the assets for pick up at our facility in East Palo Alto.

 Please confirm the eWaste vendor information, and if everything looks good, let me know so we can close out this request.

 Thanks,

 Terrence

 IT Asset Specialist
 A> Terrence Lee is responsible for approving the "IT Asset Disposal" in the provided email.

 Q> Summarize the status of the affected accounts mentioned in the following email.
 I> Subject: Affected Accounts Status 

 Date: 

 March 10, 2023 at 4:42:00 PM Eastern Standard Time
 To:

 George Nguyen 

 From:

 Peter White

 CC:

 <noinput>

 Hi George,

 The remediation process is now complete on all accounts affected by the security breach. We have reviewed and validated the fix for the custom code injection vulnerabilities on each account.

 During this time, we recommend users change their passwords on all platforms to enhance security and be on the lookout for any phishing attempts.

 Please let us know if you need further information.

 Thanks,

 Peter White

 Network Administrator
 A> The provided email indicates that the remediation process for all affected accounts is now complete, and users should change their passwords to enhance security.


 13% 13/100 [01:44<10:58,  7.57s/it]INFO 2024-06-26 20:52:36,864 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 INFO 2024-06-26 20:52:42,765 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What was the specific date when the user requested to schedule the meeting?
 I> Subject: Requirement Gathering Meeting

 Date:

 Monday, May 23, 2022 at 09:23:45 -0500

 To:

 Susan R. Stratton

 From:

 Allan Budzien

 CC:

 Daniel Furtado

 Hello Susan,

 I am writing to suggest a meeting where we can gather all the requirements for this new project. I believe that we have to consider the timeline, project scope, user stories and complete the documentation of these project essentials.

 Would it be possible to schedule this meeting a week from today? If the suggested timing does not suit you, kindly suggest a better day or time; I will then confirm the new meeting details.

 Thank you for your time and attention.

 Best regards,

 Allan
 A> The user requested to schedule the meeting a week from May 23, 2022 (the date the email was sent).


 14% 14/100 [01:57<12:14,  8.54s/it]INFO 2024-06-26 20:52:49,362 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Who is the email sent by and what is their role or relationship to the recipient, if mentioned in the email?
 I> Subject: Proposal for Marketing Collaboration

 Date:

 Thursday, September 24, 2023 at 3:46:18 PM Eastern Daylight Time

 From:

 Brian V Candler

 To:

 Ana Kosik

 Hello Ana,

 I hope this email finds you in good health. I am Brian Candler from Whitewater Marketing, and we specialize in marketing for B2B software companies. We came across your recent funding round and had a few ideas on how we could bring value to your marketing efforts.

 We have a proven track record in content marketing, product launches, and SEO. Our team is well-versed in both technical and non-technical aspects of marketing. Our expertise could complement your in-house team and bring new insights to your marketing strategy.

 We would like to request a meeting to discuss further. If you would review our work, I would be happy to send over some examples of our previous campaigns.

 Thank you for your consideration, and I look forward to hearing from you soon.

 Best,

 Brian V Candler
 A> The email was sent by Brian V Candler, who is from Whitewater Marketing. According to the context in the email, their company specializes in marketing for B2B software companies, and they reached out to Ana Kosik and her company in response to a recent funding round, suggesting a collaboration for marketing efforts.


 15% 15/100 [02:04<11:51,  8.37s/it]INFO 2024-06-26 20:52:57,153 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What are the main topics being discussed in the email?
 I> Subject: Project Status Update

 Date:

 March 16, 2023 at 11:00:00 AM Pacific Standard Time
 To:

 Alexander Mazur

 From:

 Jessica Chu

 CC:

 <noinput>

 Hi Alexander,

 I am writing to provide an update for Project Alpha.

 Quality Assurance (QA) has completed the system testing and found minor issues with the dashboard display and data visualization. The development team addressed these issues within 48 hours.

 As for the deadline, we are still on track to complete the project by the end of Q2 (on or before June 30th, 2023). I will schedule a project status meeting next Monday, March 21st, to review and discuss the current progress.

 If you have any questions, feel free to shoot me an email or give me a quick call.

 Best regards,

 Jessica Chu

 Project Manager
 A> The main topics in the email are the status update on Project Alpha, system testing with QA, identified minor issues, and the upcoming project status meeting.


 16% 16/100 [02:12<11:22,  8.13s/it]INFO 2024-06-26 20:53:04,506 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the expected delivery date of the second item on the list?
 I> Subject: Order Request

 Date:

 Friday, April 13, 2024 at 6:34:00 PM Eastern Standard Time

 From:

 Jenny Wilcox

 To:

 Chris Hammond

 Hi Chris,

 Hope you are well. I am trying to place an order today for the following items:

 Item # | Item Description | Quantity | Estimated Delivery Date
 -----|-------------------|----------|---------------------
 1 | Garmin Forerunner 745 | 2 | April 25, 2024
 2 | JBL LIVE 650BTNC Noise Canceling Headphones | 2 |
 3 | Apple iPhone 14 Pro Max Leather Case | 2 | April 16, 2024
 4 | Mophie 3-in-1 Wireless Charging Pad | 3 | April 18, 2024
 5 | Anker Powerline II USB-C to Lightning Cable | 5 | April 22, 2024

 Thank you!

 Jenny
 A> The expected delivery date for the second item on the list is not explicitly stated in the email. However, it is included in the table of items and associated quantities. Based on the table, the second item (JBL LIVE 650BTNC Noise Canceling Headphones) with a quantity of 2 has an estimated delivery date of April 15, 2024.

 Q> What is the delivery date for product #3 in the given email?
 I> Subject: Order Delivery Dates

 Date:

 Thursday, July 12, 2024 at 1:30:00 PM Eastern Standard Time

 From:

 Erin Bell

 To:

 Austin Spencer

 Hi Austin,

 Just wanted to let you know when you can expect the products you ordered to arrive.

 Product # | Product Name | Quantity | Estimated Delivery Date
 ---------|---------------|----------|---------------------
 1 | Lagavulin 16 Year Old Islay Single Malt Scotch Whisky (750mL) | 3 | July 22, 2024
 2 | Beats Studio3 Wireless Noise Canceling Over-Ear Headphones | 1 | July 16, 2024
 3 | Tissot Le Locle Automatic Co-Axial Watch | 1 |
 4 | Sonos Playbar Soundbar | 2 | July 18, 2024
 5 | Nest Learning Thermostat - 3rd Generation (Smart Learning) | 2 | July 21, 2024

 Best,

 Erin
 A> The delivery date for product #3 in the given email is not explicitly stated. However, based on the given information, product #3 is a Tissot Le Locle Automatic Co-Axial Watch with a quantity of 1, and its estimated delivery date is provided in the table: July 25, 2024.


 18% 18/100 [02:28<11:08,  8.15s/it]INFO 2024-06-26 20:53:20,869 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 INFO 2024-06-26 20:53:23,801 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Extract the recipient's name and job title from the provided email.
 I> Subject: Tuesday's 10AM Stand-up Meeting

 Date:

 Tuesday, March 15, 2022, at 10:00 AM

 From:

 Liam Smith

 To:

 Judy Martin
 Project Manager

 Dear Judy,

 Hope you are having a great day preparing for our team's stand-up meeting. First, I'd like to remind everyone to be punctual and prepare their weekly progress and challenges in 5 minutes format.

 Next, I am looking forward to hearing from James and George regarding the cyber security architecture draft we discussed last week. Also, Sarah should be sharing an update on the pending approvals for our current project.

 Thanks,

 Liam
 A> The recipient's name is Judy Martin, and her job title is Project Manager.

 Q> What is the new password suggested by the support team for the user?
 I> Subject: New Password Request

 Date:

 Wednesday, November 24, 2021 at 11:51:39 AM Eastern Standard Time

 From:

 Kelly's IT Support

 To:

 Kelly.Ware

 Hi Kelly,

 Please find below the new temporary password for your email account:

 New password: N3wP@55w0rd_K3LLY

 You'll be prompted to change it when you first sign in.

 Should you require any assistance, please contact the IT helpdesk.

 Best,
 Kelly's IT Support
 A> The new password suggested by the support team for the user is N3wP@55w0rd\_K3LLY.


 20% 20/100 [02:44<10:40,  8.00s/it]INFO 2024-06-26 20:53:36,363 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 INFO 2024-06-26 20:53:41,898 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the outcome of the request for Manager's approval?
 I> Subject: Ad Hoc Request Approval

 Date:

 Friday, August 10, 2024 at 9:00:00 AM Eastern Standard Time

 From:

 Shawna Pike

 To:

 Jason McCaffrey

 Hi Jason,

 I wanted to request your approval for the Ad Hoc Request for R&D funding from the Science committee. The deadline for submission is tomorrow, and it is an urgent matter.

 Best,

 Shawna
 A> The outcome of the request for Manager's approval is not explicitly stated in the email. However, based on the given information, Shawna Pike requested Jason McCaffrey's approval for an Ad Hoc request for R&D funding from the Science committee by August 11, 2024. The response from Jason McCaffrey is not provided in the email.

 Q> What is the total amount of the requested R&D funding?
 I> Subject: Request for R&D Funding

 Date:

 Thursday, August 9, 2024 at 11:00:00 AM Eastern Standard Time

 From:

 Jason McCaffrey

 To:

 Meghan Barrie

 Hi Meghan,

 I am requesting R&D funding for our department for the fiscal year of 2025. The total amount requested is $250,000.

 Best,

 Jason
 A> The total amount of the requested R&D funding is $250,000.


 22% 22/100 [03:02<10:52,  8.36s/it]INFO 2024-06-26 20:53:54,462 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the action requested by the sender in the provided email?
 I> Subject: Request for Training Materials

 Date:

 Tuesday, February 14, 2023 at 6:15:48 AM EST

 To:

 Josephine Granville

 From:

 Elliott Middleton

 CC:

 <noinput>

 Hello Josephine,

 I hope this email finds you well. I would like to request the training materials we discussed for the ACME project that's starting next month.

 The new team members would greatly benefit from reviewing them ahead of time, as it will significantly shorten the onboarding process and allow us to jumpstart production.

 I appreciate your support in this matter.

 Best regards,

 Elliott Middleton

 Project Manager
 A> The action requested by the sender, Elliott Middleton, is to provide the training materials for the ACME project ahead of time.

 Q> What is the primary concern expressed by the sender regarding the assigned tasks?
 I> Subject: Deadline Extension Request: Due Diligence Documents

 Date:

 Thursday, January 26, 2023 at 1:00:15 PM EST

 To:

 Cameron Rolfe

 From:

 Jamie Downs

 CC:

 <noinput>

 Dear Cameron,

 I trust you are doing well. I am writing to discuss the assigned due diligence documents for the Hillside Gardens project.

 Regrettably, I am behind schedule due to unexpected complications with the permits and zoning variances. Therefore, I request an extension of one week to ensure that a thorough evaluation is conducted.

 Apologies for the inconvenience. I am committed to providing a comprehensive report within that time frame.

 Thank you for your understanding.

 Best regards,

 Jamie Downs
 A> The primary concern expressed by the sender, Jamie Downs, is that unexpected complications with permits and zoning variances have caused a delay in completing the assigned due diligence documents, requiring a one-week extension.


 24% 24/100 [03:16<10:01,  7.91s/it]INFO 2024-06-26 20:54:08,443 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Clarify the reason for the delay in the lab receiving monitors, as conveyed in the email.
 I> 
 A> The email indicates that the lab's delay in receiving monitors was due to an additional round of the testing process to ensure high quality.

 Q> Which priority project or initiative, mentioned in the email, has caused the priority level of other work to lower?
 I> Subject: Project X Urgent Update

 Date:

 Tuesday, March 26, 2024 at 1:40:00 PM Eastern Standard Time

 From:

 Dr. Leonard Boniface

 To:

 Hermann Ruprecht

 Hi Hermann,

 I am writing to provide you an important update regarding Project X. Due to this now being the top priority, it will inevitably affect the priority of other projects with deadlines and milestones.

 Best,

 Dr. Leonard Boniface
 A> The Project X mentioned in the email has caused the priority level of other projects to lower, as it is the top priority initiative at present.


 26% 26/100 [03:27<08:47,  7.12s/it]INFO 2024-06-26 20:54:19,340 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> For the given email, what is the reason for the request of a meeting later in the week?
 I> Subject: Request for a Meeting

 Date:

 Monday, December 13, 2021 at 9:30:00 AM CST

 From:

 Jonathan Martin

 To:

 Bethany McKenzie

 CC:

 <noinput>

 Hi Bethany,

 I hope you are doing well. I was wondering if we could schedule a short meeting sometime later this week. I received the updated financial report for our department and would like to discuss it with you.

 Let me know if that works for you and I will send over some date options.

 Best,

 Jonathan
 A> The reason for the request of a meeting later in the week, as mentioned in the given email, is to discuss the updated financial report for the department with Bethany.


 27% 27/100 [03:33<08:30,  7.00s/it]INFO 2024-06-26 20:54:25,798 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Which subordinate's name has been mentioned in the email for updating the manager on the approval process?
 I> Subject: Request for Equipment Approval

 Date:

 July 12, 2021 at 4:23:00 PM EDT

 From:

 John Wallace

 To:

 Holly McShane

 Hi Holly,

 I'm writing to request approval for new equipment for team members who need them for the new project. I've noted all necessary details in the attached document, including costs, time frames, and the team members who need the equipment.

 Could you please review and provide feedback by end of day tomorrow? I'd appreciate it if Sarah could provide an update on the pending approvals for our current project as well.

 Thanks,

 John
 A> Sarah has been mentioned in the email for updating the manager on the approval process for the new equipment request.

 Q> Identify the main topics discussed during the meeting according to the email.
 I> Subject: Meeting Summary: R&D Project Updates

 Date:

 Wednesday, June 2, 2021 at 2:07:25 PM Eastern Standard Time

 From:

 Jack Graham

 To:

 Team Members

 Hello Team,

 Here's the summary from today's R&D meeting:

 1. Machine Learning project: Finalizing the testing phase. Expecting to launch in beta within 2 weeks.

 2. Robotics project: Testing phase had bugs, which have been resolved. Updating the launch timeline for review.

 3. AI in Space project: All data has been collected and projects are on schedule.

 Please follow up with any questions or concerns.
 A> The main topics discussed in the meeting include the Machine Learning project, the Robotics project, and the AI in Space project.


 29% 29/100 [03:46<08:03,  6.81s/it]INFO 2024-06-26 20:54:38,720 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Summarize the resolution that the email's author proposes to address the issue.
 I> Subject: High-Def Monitor Update

 Date:

 Friday, February 23, 2024 at 9:13:32$_{ }$PM Eastern Standard Time

 From:

 Luke Inglis

 To:

 Kate Soule

 Hi Kate,

 I am writing to explain to you the delay in our lab receiving monitors. We have now finally reached number 11 in this process, which is the point at which the monitors are shipped to our location. However, there has been confusion regarding the delivery date for the Odyssey Ark 55-inch monitor. The supplier is located in Europe and thought that 5/10/2024 was actually 10/5/2024. As a result, the monitor is not expected to arrive until May 10, 2024, which is later than expected. I apologize for the confusion.

 Regards,

 Luke Inglis

 Operations Manager AI Models & MIT-IBM Watson AI Lab IBM Research
 A> The email's author, Luke Inglis, proposes to address the issue by acknowledging the delay and apologizing for the confusion regarding the delivery date of the Odyssey Ark 55-inch monitor. However, he does not propose a specific resolution to this issue in the email.

 Q> What is the reason for the delay that was not initially anticipated?
 I> Subject: High-Def Monitor Update

 Date:

 Friday, February 23, 2024 at 9:13:32$_{ }$PM Eastern Standard Time

 From:

 Luke Inglis

 To:

 Kate Soule

 Hi Kate,

 I am writing to explain to you the delay in our lab receiving monitors. On Dec 2$^{nd,}$ 2023, I started the process of purchasing 7 high-def Samsung monitors for the MIT-IBM Watson AI Lab. We have now finally reached number 11 in this process, which is the point at which the monitors are shipped to our location. However, there has been confusion regarding the delivery date for the Odyssey Ark 55-inch monitor. The supplier is located in Europe and thought that 5/10/2024 was actually 10/5/2024. As a result, the monitor is not expected to arrive until May 10, 2024, which is later than expected. I apologize for the confusion.

 Regards,

 Luke Inglis

 Operations Manager AI Models & MIT-IBM Watson AI Lab IBM Research
 A> The reason for the delay that was not initially anticipated is confusion regarding the delivery date for the Odyssey Ark 55-inch monitor. The supplier, who is located in Europe, thought that 5/10/2024 was actually 10/5/2024, which caused the monitor to be shipped later than expected and delayed its arrival until May 10, 2024.


 31% 31/100 [04:02<08:14,  7.16s/it]INFO 2024-06-26 20:54:54,457 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the main reason for the account termination request in this email?
 I> Subject: Account Termination Request

 Date:

 Thursday, March 17, 2022 at 1:35:16 PM Central Standard Time

 From:

 David Church

 To:

 Executive Team

 Dear Executive Team,

 I am writing to formally request the termination of the Pro account for client XYZ, account number P-000123. I am the account administrator for this account and I appreciate your consideration of my request.

 Reason for Termination:

 XYZ has consistently failed to meet the acceptable terms of use for our product. This violation of policy has led to misuse of the account, causing negative impacts to our network security and resources.

 Next Steps:

 Please confirm receipt of this request and let me know the expected timeline for processing.

 Thank you for your time and assistance,

 David Church

 Account Administrator
 A> The main reason for the account termination request is due to XYZ's consistent failure to meet the acceptable terms of use for the product. This violation of policy has led to misuse of the account, which affects the network security and resources negatively. David Church, the account administrator, is requesting the termination of the Pro account for the specific client.


 32% 32/100 [04:09<08:08,  7.18s/it]INFO 2024-06-26 20:55:01,735 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Identify the sender's role and organization from the email signature to establish their credibility and connection to the recipient.
 I> Subject: High-Def Monitor Update

 Date:

 Friday, February 23, 2024 at 9:13:32 PM Eastern Standard Time

 From:

 Luke Inglis

 To:

 Kate Soule

 Hi Kate,

 I am writing to explain to you the delay in our lab receiving monitors.

 ...

 Regards,

 Luke Inglis

 Operations Manager AI Models & MIT-IBM Watson AI Lab
 IBM Research
 A> The sender, Luke Inglis, is an Operations Manager at AI Models & MIT-IBM Watson AI Lab, a part of IBM Research. This information establishes his credibility and connection to the recipient, Kate Soule, within the context of the monitor order and delivery update.

 Q> What are the estimated arrival dates for the five monitors mentioned in the table in the email?
 I> Subject: High-Def Monitor Update

 Date:

 Friday, February 23, 2024 at 9:13:32 PM Eastern Standard Time

 From:

 Luke Inglis

 To:

 Kate Soule

 Hi Kate,

 I am writing to explain to you the delay in our lab receiving monitors.

 ...

 Regards,

 Luke Inglis

 Operations Manager AI Models & MIT-IBM Watson AI Lab
 IBM Research

 <noinput>
 A> The estimated arrival dates for the five monitors mentioned in the table in the email are:

 1. Odyssey Ark 55-inch: 5/10/2024
 2. Odyssey G7 32-Inch (2 units): 3/7/2024
 3. Odyssey G55C 27-Inch (2 units): 2/27/2024


 34% 34/100 [04:22<07:40,  6.97s/it]INFO 2024-06-26 20:55:14,898 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Who is responsible for next steps concerning the report and when is it due?
 I> Subject: Report deadlines and takeaways

 Date:

 Wednesday, November 17, 2021 at 8:35:56 PM Eastern Standard Time

 From:

 David Ferguson

 To:

 Team Members

 Hi all,

 Please find the report deadlines and corresponding takeaways attached.

 Mark - you will be responsible for the marketing section and it's due on Monday 11:59 PM.

 Samir - you will be responsible for the engineering section and it's due on Wednesday 11:59 PM.

 Jessica - you will be responsible for the design section and it's due on Thursday 11:59 PM.

 Thank you!

 David
 A> Mark is responsible for the marketing section of the report and it's due next Monday at 11:59 PM.

 Q> What is the major concern discussed in the email related to the construction project?
 I> Subject: Important Notification: Construction Project Update

 Date:

 Tuesday, February 1, 2022 at 4:51:12 PM Eastern Standard Time

 From:

 Frank Richards

 To:

 Site Engineers

 Hi Team,

 Had a discussion with our stakeholders regarding the construction project. Unfortunately our current supply chain bottlenecks have impacted our ability to deliver on time. This is causing delays in completing work due to a shortage of materials. We're looking into alternatives and exploring different suppliers.

 Could you update the timeline accordingly and notify all relevant parties of the expected delays?

 Thanks,

 Frank
 A> The major concern discussed in the email related to the construction project is the encountering of supply chain bottlenecks causing delays in completing work due to shortage of materials.


 36% 36/100 [04:35<07:15,  6.81s/it]INFO 2024-06-26 20:55:27,896 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the new management tool that Rick plans to implement in the email?
 I> Subject: New Management System Implementation

 Date:

 Thursday, November 17, 2022 at 11:32:22 AM Eastern Standard Time

 From:

 Rick Stevens

 To:

 All Admin Staff

 Hi Team,

 I am considering implementing a new management tool called Teamwork that will be beneficial for our admin team. It will improve the team's efficiency, collaboration, and workload management.

 ...

 Thanks,

 Rick Stevens
 Assistant Manager
 A> The new management tool that Rick plans to implement is called Teamwork.

 Q> Who are the main stakeholders responsible for reviewing the attached report in the email?
 I> Subject: Performance Report for Quarterly Review

 Date:

 Tuesday, March 15, 2022 at 4:11:16 PM Eastern Standard Time

 From:

 Jackson Lin

 To:

 Financial Planning Team, Legal Department, Department of Operations

 Attached:

 Financial Performance Report

 Hi All,

 Please find the Q1 2022 Financial Performance Report attached. Kindly review and provide feedback to the Finance team accordingly.

 Best,

 Jackson Lin
 Finance Manager
 A> The main stakeholders responsible for reviewing the attached report in the email are the Financial Planning Team, the Legal Department, and the Department of Operations.


 38% 38/100 [04:47<06:42,  6.50s/it]INFO 2024-06-26 20:55:39,582 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Identify the sender's email address to track the origin of the message.
 I> Subject: Request for Feedback on AI Model

 Date:

 Friday, May 31, 2024 at 7:35:09 PM Eastern Daylight Time
 From:

 <noinput>

 To:

 David Morales
 CC:

 <noinput>

 David,

 I hope this email finds you well. I am writing to request feedback on the new AI model we developed last month.

 The model is designed for use in manufacturing to improve productivity and product quality. Your feedback is valuable to help us make improvements and further optimize the model for real-world applications.

 Please find the link to the feedback form below.

 [AI Model Feedback Form](https://research-survey.ibm.com/r/4GK3BNWE)

 Please provide your input by Friday, June 7th, 2024. If you have any questions, don't hesitate to ask, and I would be happy to help.

 Thank you for your time and support.

 Best regards,

 William R. Adams III

 IBM Research AI Team
 A> The sender's email address is "[[email protected]](mailto:[email protected])".

 Q> Determine the timeline for the project by identifying the deadline in the email.
 I> <noinput>

 Subject: Project Invoice

 Date:

 Wednesday, June 19, 2024 at 3:17:22 PM Eastern Standard Time
 From:

 ALLEN CONSULTING GROUP

 To:

 Barnes & Noble
 CC:

 <noinput>

 Dear Barnes & Noble,

 I am writing to follow up on the project invoice for our collaboration (May 15th - June 15th, 2024).

 The total project cost came to $52,700, with the following invoice breakdown:

 - Project Management: $9,200
 - Technical Support: $9,000
 - Software Licenses: $34,500

 As stated in our agreement, the payment deadline is 30 days from the invoice date. In this case, the deadline falls on July 17th, 2024.

 If you need any additional information, please feel free to contact me directly at <span style="color:#2a6496;">[[email protected]](mailto:[email protected])</span>.

 Thank you for your prompt attention to this matter.

 Best regards,

 Lora Allen

 ALLEN CONSULTING GROUP

 Senior Project Manager
 A> The deadline for the project is July 17th, 2024.


 40% 40/100 [05:03<06:56,  6.94s/it]INFO 2024-06-26 20:55:55,357 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the main topic of the email and what subtopics are mentioned in relation to the main topic?
 I> Subject: Employee Code of Conduct Reminder

 Date:

 Wednesday, March 13, 2024 at 11:23:54 AM Eastern Standard Time

 From:

 David Marshall

 To:

 All Employees

 Dear All,

 As a reminder, we would like to emphasize the significance of upholding our company's code of conduct at all times.

 1. Conflict of Interest - Avoid any situation where your personal interests may conflict with the best interests of the company.
 2. Ethics - Maintain ethical standards in all aspects of your work, including relationships with suppliers and customers.
 3. Data Protection - Do not disclose any confidential or sensitive business information to unauthorized parties.
 4. Outside Activities - Ensure that any outside activities do not interfere with your job performance or conflict with the company's policies.

 Please review the code of conduct carefully and ensure that you adhere to it at all times.

 Best regards,

 David Marshall

 HR Director
 A> The main topic of the email is a reminder of the company's code of conduct for all employees. The subtopics mentioned in relation to the main topic are:

 * Conflict of Interest
 * Ethics
 * Data Protection
 * Outside Activities


 41% 41/100 [05:13<07:26,  7.56s/it]INFO 2024-06-26 20:56:05,672 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Deduce the intended action from the sender after describing a problem in the email.
 I> Subject: Shipping Issue

 Date:

 Thursday, March 21, 2024 at 11:30:55 AM Eastern Daylight Time

 From:

 Emily Williams

 To:

 David Green

 CC:

 <noinput>

 Dear David,

 I have just been informed by our warehouse team that one of the critical components needed for the security system installations has been damaged in transit. We are currently working on getting a replacement part, but it may take an extra two days to ship and reach our site.

 Best,

 Emily Williams

 Logistics Coordinator
 A> The intended action from the sender is to inform David Green of the shipping issue with a critical component for the security system installations and to assure that they are working on a replacement part, which might take an extra two days to ship and reach their site.

 Q> Determine the email recipient's responsibilities based on the sender's instructions or expectations.
 I> Subject: Weekly SWE Meeting Cancellation

 Date:

 Tuesday, September 12, 2023 at 11:52:25 AM Eastern Daylight Time

 From:

 Patricia Zhang

 To:

 James Burton

 CC:

 <noinput>

 Hi James,

 Due to a few team members being out sick, I would like to cancel this week's Software Engineering (SWE) meeting, which was scheduled for Friday 3 PM ET. Request you to notify other team members about the cancellation.

 Thanks,

 Patricia Zhang

 Software Engineering Manager
 A> Based on the email, the recipient, James Burton, is responsible for notifying other SWE team members about the cancellation of this week's scheduled meeting.


 43% 43/100 [05:26<06:51,  7.22s/it]INFO 2024-06-26 20:56:18,802 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What are the requested items for the upcoming conference from the email?
 I> Subject: Conference Supplies Request

 Date:

 Wednesday, August 18, 2021 at 11:34:00 AM EDT

 From:

 Jackie Davis

 To:

 Marketing Department

 CC:

 <noinput>

 Hello Marketing Department,

 I hope this email finds you well. I would like to request the following items for the upcoming conference on August 25:

 * 500 branded pens
 * 200 notepads
 * 100 reusable water bottles
 * 5 large pop-up banners
 * 5 roller banners
 * A shipment of flyers from the latest campaign

 If there are any issues, please let me know as soon as possible.

 Best regards,
 Jackie Davis
 A> The requested items for the upcoming conference from the email are 500 branded pens, 200 notepads, 100 reusable water bottles, 5 large pop-up banners, 5 roller banners and a shipment of flyers from the latest campaign.


 44% 44/100 [05:39<07:46,  8.33s/it]INFO 2024-06-26 20:56:31,647 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Extract the primary topic from the email to help focus further investigation or communication.
 I> Subject: Conference Room Calendar and Space Management

 Date:

 Friday, July 8, 2022 at 2:15:52 PM Eastern Standard Time

 From:

 Charles Payne

 To:

 Finance Team
 CC:

 Martin Markham

 Lisa Caldwell

 Dear Team,

 Our current conference room calendar and space management system is outdated and in need of an upgrade. I am happy to announce that we are now in the process of purchasing a state-of-the-art space management software.

 ...

 Regards,

 Charles Payne

 Facilities Manager
 A> The main topic of the email is the outdated conference room calendar and space management system and the upcoming acquisition of its upgraded version.

 Q> Recognize the requested action to be taken by collecting relevant information about the request details within the email.
 I> Subject: Document Approval Request

 Date:

 Tuesday, December 13, 2022 at 4:53:36 PM Eastern Standard Time

 From:

 Jack Steward

 To:

 John Brady

 Dear John,

 As we discussed earlier, I am attaching the final draft of our project proposal for the Smith & Wesson account. I would appreciate it if you could approve the document and forward it to Mike Cronin by EOD tomorrow.

 Best,

 Jack Steward

 Assistant Project Manager
 A> The requested action is to review and approve the project proposal document for the Smith & Wesson account and forward it to Mike Cronin by EOD tomorrow.


 46% 46/100 [05:51<06:45,  7.50s/it]INFO 2024-06-26 20:56:43,734 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the deadline set by the project manager for the completion of the deliverables mentioned in the email?
 I> Subject: Project Update: Web Design and Development

 Date:

 Thursday, February 17, 2022 at 10:54:21 AM Eastern Standard Time

 From:

 Kimberly Lee

 To:

 Web Development Team

 Hi Web Development Team,

 Please find the project update attached. We aim to complete the design and development by the end of next month.

 Best,

 Kimberly Lee
 Project Manager
 A> The deadline set by the project manager for the completion of the deliverables mentioned in the email is the end of next month.

 Q> What is the status of the inventory mentioned in the email?
 I> Subject: Inventory Update: Monthly Summary

 Date:

 Monday, January 3, 2022 at 11:10:05 AM Eastern Standard Time

 From:

 Robey Kwok

 To:

 Warehouse Management Team

 Hello Warehouse Team,

 Please find the monthly inventory update attached. Our current inventory count is 12,500 units and we are on track to meet the demand for the upcoming quarter.

 Best,

 Robey Kwok
 Inventory Manager
 A> The status of the inventory mentioned in the email is that the current inventory count is 12,500 units and they are on track to meet the demand for the upcoming quarter.


 48% 48/100 [06:03<06:05,  7.03s/it]INFO 2024-06-26 20:56:55,924 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the reason given for the account termination request in the email?
 I> Subject: Account Termination Request

 Date:

 Thursday, March 17, 2022 at 1:35:16 PM Central Standard Time

 From:

 David Church

 To:

 Executive Team

 Dear Executive Team,

 I am writing to formally request the termination of the Pro account for client XYZ, account number P-000123. I am the account administrator for this account and I appreciate your consideration of my request.

 Reason for Termination:

 XYZ has consistently failed to meet the acceptable terms of use for our product. This violation of policy has led to misuse of the account, causing negative impacts to our network security and resources.

 Next Steps:

 Please confirm receipt of this request and let me know the expected timeline for processing.

 Thank you for your time and assistance,

 David Church

 Account Administrator
 A> The specified account is requested to be terminated because the client has consistently failed to meet the terms of use for the product. The violation of policy has led to the misuse of the account, negatively impacting the network security and resources.

 Q> What are the expected next steps for the account termination request provided?
 I> Subject: Account Termination Request

 Date:

 Thursday, March 17, 2022 at 1:35:16 PM Central Standard Time

 From:

 David Church

 To:

 Executive Team

 Dear Executive Team,

 I am writing to formally request the termination of the Pro account for client XYZ, account number P-000123. I am the account administrator for this account and I appreciate your consideration of my request.

 Reason for Termination:

 XYZ has consistently failed to meet the acceptable terms of use for our product. This violation of policy has led to misuse of the account, causing negative impacts to our network security and resources.

 Next Steps:

 Please confirm receipt of this request and let me know the expected timeline for processing.

 Thank you for your time and assistance,

 David Church

 Account Administrator
 A> The expected next steps include confirming receipt of the request and informing the requester of the expected timeline for processing the account termination request.


 50% 50/100 [06:17<05:50,  7.02s/it]INFO 2024-06-26 20:57:09,923 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Identify the key points in the provided email discussing project updates.
 I> Subject: Project Updates

 Date:

 Friday, March 18, 2022, at 3:45 PM

 From:

 Ryan Cruise

 To:

 Aleem Ali
 David Williams

 Hi Aleem, David,

 I hope this email finds you well. I wanted to provide a quick update on the AI project:

 * The design phase of the AI model is nearly complete, and it's looking promising. We will start implementing it in the coming week.
 * Alexis and Taylor have been working on the machine learning algorithms, and we are seeing great outcomes.
 * For the data collection phase, Alexis and Mitchell are creating a new tool to automate data extraction that will save us a lot of time going forward.
 * For the presentation, we will have a demo ready in two weeks.

 Best,

 Ryan
 A> The project updates include the following points: 
 1. The design phase of the AI model is nearly complete.
 2. Implementation of the AI model will start in the coming week.
 3. Alexis and Taylor have been working on the machine learning algorithms with positive results.
 4. Alexis and Mitchell are creating a new tool to automate data extraction.
 5. A demo will be ready in two weeks.

 Q> Who is responsible for creating a new tool to automate data extraction in the AI project?
 I> 
 A> Alexis and Mitchell are responsible for creating a new tool to automate data extraction in the AI project.


 52% 52/100 [06:29<05:22,  6.72s/it]INFO 2024-06-26 20:57:22,075 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Who is the manager who must approve the purchase?
 I> Subject: Lab Instruments Procurement

 Date:

 Monday, October 7, 2024 at 4:29:43 PM Eastern Standard Time

 From:

 Denise Hightower

 To:

 Benjamin Donnelly

 Hi Ben,

 As we discussed last Friday, please proceed with procuring the three units of the Carl Zeiss lab microscope. Before sending the purchase order to Procurement, the Manager needs to approve it. I am sending you a quote for your reference.

 Best,

 Denise
 A> The manager who must approve the purchase of the Carl Zeiss lab microscope is Benjmain Donnelly.

 Q> What are the revised arrival dates for the two Odyssey G7 32-Inch monitors?
 I> Subject: Updated Shipping Schedule

 Date:

 Wednesday, February 28, 2024 at 7:15:21 AM Eastern Standard Time

 From:

 Luke Inglis

 To:

 Kate Soule

 Hi Kate,

 The revised arrival dates for the two Odyssey G7 32-Inch monitors are March 10th, 2024, and March 17th, 2024.

 Best,

 Luke
 A> The revised arrival dates for the two Odyssey G7 32-Inch monitors are March 10th, 2024, and March 17th, 2024.


 54% 54/100 [06:42<05:00,  6.53s/it]INFO 2024-06-26 20:57:34,289 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> To whom is the given email from Jack Mosley sent?
 I> Subject: Request for Design File

 Date:

 Monday, December 6, 2021 at 11:35:50 AM Eastern Standard Time

 From:

 Jack Mosley

 To:

 AutoCAD Support Team

 Hi,

 I submitted a request for the design file for the Vinyl siding project yesterday. It’s urgent. Have you found it yet? Could you please send it over?

 Thanks,

 Jack
 A> The given email from Jack Mosley is sent to the AutoCAD Support Team.

 Q> What are the expected deliverables mentioned in the email from Kelly Sweeten?
 I> Subject: Contract Documentation and Deliverables

 Date:

 Wednesday, July 14, 2021 at 12:06:14 PM Eastern Standard Time

 From:

 Kelly Sweeten

 To:

 Software Development Team

 Hi Everyone,

 As per the contract, the deliverables include a UI/UX report, fully functional software, test case documents and user manuals. Please make sure all these are completed and delivered to the stakeholders within the deadline.

 Thanks,

 Kelly
 A> The expected deliverables mentioned in the email from Kelly Sweeten are a UI/UX report, fully functional software, test case documents, and user manuals.


 56% 56/100 [06:53<04:36,  6.29s/it]INFO 2024-06-26 20:57:45,830 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Which projects are currently on hold and why?
 I> Subject: Project status update

 Date:

 Tuesday, February 8, 2022 at 10:00:00 AM Eastern Standard Time

 From:

 Taylor Lanier

 To:

 Project Managers

 Hello Team,

 I regret to inform you that due to budget constraints, there will be a temporary freeze on the following projects:

 - Project A: Green Building Technology (3-month hold)
 - Project B: Solar Infrastructure (2-month hold)

 Please make necessary arrangements and communicate to the team.

 Best,

 Taylor
 A> Project A: Green Building Technology is currently on hold for a duration of 3 months, and Project B: Solar Infrastructure is also paused for 2 months. The reason for this halt is budget constraints, as mentioned in the email.

 Q> What relevant details are shared regarding the new client joining the company?
 I> 
 A> No specific input is provided for this instruction. The response would depend on the given email. In general, relevant details shared may include the new client's identification (name, position, organization, etc.), the reason for joining, or any other information directly related to the new client.


 58% 58/100 [07:04<04:16,  6.10s/it]INFO 2024-06-26 20:57:57,169 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Can you summarize Jack's request and his current status with it?
 I> Subject: Request for Design File

 Date:

 Monday, December 6, 2021 at 11:35:50 AM Eastern Standard Time

 From:

 Jack Mosley

 To:

 AutoCAD Support Team

 Hi,

 I submitted a request for the design file for the Vinyl siding project yesterday. It’s urgent. Have you found it yet? Could you please send it over?

 Thanks,

 Jack
 A> Jack Mosley requested the design file for the Vinyl siding project yesterday and it is still pending. He finds it urgent.

 Q> What is the expected delivery date for the Odyssey Ark 55-inch monitor?
 I> Subject: High-Def Monitor Update

 Date:

 Friday, February 23, 2024 at 9:13:32$_{ }$PM Eastern Standard Time

 From:

 Luke Inglis

 To:

 Kate Soule

 Hi Kate,

 I am writing to explain to you the delay in our lab receiving monitors. On Dec 2$^{nd,}$ 2023, I started the process of purchasing 7 high-def Samsung monitors for the MIT-IBM Watson AI Lab. We have now finally reached number 11 in this process, which is the point at which the monitors are shipped to our location. However, there has been confusion regarding the delivery date for the Odyssey Ark 55-inch monitor. The supplier is located in Europe and thought that 5/10/2024 was actually 10/5/2024. As a result, the monitor is not expected to arrive until May 10, 2024, which is later than expected. I apologize for the confusion.

 Regards,

 Luke Inglis

 Operations Manager AI Models & MIT-IBM Watson AI Lab IBM Research
 A> The Odyssey Ark 55-inch monitor is expected to arrive on May 10, 2024.


 60% 60/100 [07:18<04:13,  6.33s/it]INFO 2024-06-26 20:58:10,870 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Summarize the key points from the email for better understanding and retention.
 I> Subject: Project Update Meeting

 Date:

 Monday, December 5, 2022 at 1:01:02 PM Eastern Standard Time

 From:

 Alex Feinberg

 To:

 Marketing Team

 Hi marketing team,

 Just a quick update on the upcoming project meeting:

 - Date: Thursday, December 8, 2022
 - Time: 2-3:30 pm ET
 - Location: Conference Room B
 - Agenda:
  - Project 1 progress report
  - Feedback on Market Analysis Survey
  - Client's response to our proposal

 Looking forward to seeing you all there!

 Best,

 Alex Feinberg
 Marketing Manager
 A> The project update meeting is on Thursday, December 8, 2022, from 2 pm to 3:30 pm ET, in Conference Room B. The team will discuss the progress of Project 1, feedback on the Market Analysis Survey, and the client's response to the proposal.


 61% 61/100 [07:25<04:11,  6.45s/it]INFO 2024-06-26 20:58:17,845 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the latest product delivery date mentioned in the email?
 I> Subject: Order confirmation and delivery update

 Date:

 Friday, April 29, 2022 at 2:30:51 PM Eastern Standard Time

 From:

 Donna Thompson

 To:

 Customer Service

 CC:

 [Customer Name]

 Dear [Customer Name],

 Thank you for your order! It has been processed and is ready for shipment. We expect to deliver your order by May 15, 2022.

 Best regards,

 Donna Thompson
 Customer Care Associate
 A> The latest product delivery date mentioned in the email is May 15, 2022.

 Q> What is the policy related to employee vacations as discussed in the given email?
 I> Subject: HR Updates

 Date:

 Thursday, March 3, 2022 at 12:15:00 PM Eastern Standard Time

 From:

 Lisa Johnson

 To:

 All Employees

 Hello Team,

 As summer approaches, we'd like to remind everyone about our company's vacation policy. All employees are encouraged to take at least two weeks off per year to maintain a healthy work-life balance.

 Remember, vacation time is essential for your overall well-being and productivity. Please plan accordingly with your supervisor.

 Best,

 Lisa
 HR Manager
 A> The email discusses the company's vacation policy, which encourages all employees to take at least two weeks off per year for better work-life balance and overall well-being. Employees should plan their vacation time with their supervisor.


 63% 63/100 [07:37<03:55,  6.35s/it]INFO 2024-06-26 20:58:30,192 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the issue reported by James, and what does he propose to do about it?
 I> Subject: Network Issue

 Date:

 Thursday, September 23, 2021 at 8:00:00 AM Eastern Standard Time

 From:

 James Carrington

 To:

 Network Support Team

 CC:

 <noinput>

 Hi Team,

 I'm reporting a network issue in the London datacenter. Machines connected to subnet 10.100.201.0/24 are unreachable via the primary VLAN. I suspect there's an issue with the core switch.

 I propose to investigate if there's a physical link failure, check the associated routing & switching policies, and monitor the neighbor relationships.

 Best,

 James Carrington
 Senior Infrastructure Engineer
 A> James Carrington reported a network issue in the London datacenter affecting machines on subnet 10.100.201.0/24. He suspects a core switch problem and proposed investigating physical link failure, reviewing routing & switching policies, and monitoring neighbor relationships.

 Q> What steps are needed to be taken in order to proceed with the plan proposed by Jill in the email?
 I> Subject: Marketing Strategy

 Date:

 Friday, May 13, 2022 at 10:00:00 AM Eastern Standard Time

 From:

 Jill Singh

 To:

 Marketing Team

 CC:

 Operations Team

 Hi Team,

 I propose we create a campaign for product x focusing on the ABC industry. We'd start the campaign with a teaser followed by a full product release and information, leading to a Q&A webinar with experts.

 Best,

 Jill Singh
 Marketing Director
 A> To proceed with Jill's proposed marketing strategy for product x in the ABC industry, the steps include:

 1. Create a campaign teaser
 2. Release full product information
 3. Schedule a Q&A webinar with experts

 Collaboration with the Operations Team is also necessary to ensure successful execution.


 65% 65/100 [07:51<03:46,  6.48s/it]INFO 2024-06-26 20:58:43,706 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> To whom did the sender of the email schedule the meeting?
 I> Subject: Project Meeting

 Date:

 Monday, April 25, 2022 at 10:28:28 AM Eastern Daylight Time

 From:

 John Doe

 To:

 Samantha Rogers, Michael Brown

 Hi Samantha and Michael,

 I'd like to schedule our project meeting for this Thursday at 11:00 AM.

 Please let me know your availability for the rest of the week.

 Best,

 John Doe

 Project Lead

 <noinput>
 A> The sender of the email, John Doe, scheduled the meeting for Samantha Rogers and Michael Brown.

 Q> What is the name of the proposed vendor, and what are they expected to provide in the given email?
 I> Subject: Proposal for Office Supplies

 Date:

 Thursday, May 12, 2022 at 2:45:16 PM Eastern Daylight Time

 From:

 Jonathan Lee

 To:

 Procurement Team

 Hi Procurement,

 We have received a proposal from a company called NextGen Office Supplies, which has offered to provide us with discounted stationery items such as pens, paper, and folders.

 I suggest we consider this vendor, as they may help us cut down on office supply expenses.

 Best,

 Jonathan Lee

 Office Manager

 <noinput>
 A> The name of the proposed vendor is NextGen Office Supplies, and they are expected to provide discounted stationery items such as pens, paper, and folders.


 67% 67/100 [08:03<03:31,  6.40s/it]INFO 2024-06-26 20:58:56,150 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Who is the sender of the email and what is the subject of the message about?
 I> Date:

 Thursday, March 15, 2024 at 4:12:17 PM Eastern Standard Time

 From:

 Yvonne Bishop

 To:

 Michael Emerson, Jason Hicks, and Maria Rodriguez

 Subject: Design presentation next week

 Hello everyone,

 I wanted to reach out to let you know that I have scheduled the design presentation for next Wednesday at 1:00 PM.

 Best,

 Yvonne Bishop
 A> The sender of the email is Yvonne Bishop and the subject of the message is about a design presentation next week.


 68% 68/100 [08:09<03:22,  6.32s/it]INFO 2024-06-26 20:59:02,129 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Identify the date when the minor issues in the dashboard display and data visualization were resolved.
 I> Subject: Project Status Update

 Date:

 March 16, 2023 at 11:00:00 AM Pacific Standard Time
 To:

 Alexander Mazur

 From:

 Jessica Chu

 CC:

 <noinput>

 Hi Alexander,

 I am writing to provide an update for Project Alpha.

 Quality Assurance (QA) has completed the system testing and found minor issues with the dashboard display and data visualization. The development team addressed these issues within 48 hours.

 As for the deadline, we are still on track to complete the project by the end of Q2 (on or before June 30th, 2023). I will schedule a project status meeting next Monday, March 21st, to review and discuss the current progress.

 <noinput>
 A> The minor issues in the dashboard display and data visualization were resolved within 48 hours after being identified by the QA team.

 Q> Reveal the status of the project's deadline as mentioned in the email.
 I> Subject: Project Status Update

 Date:

 March 16, 2023 at 11:00:00 AM Pacific Standard Time
 To:

 Alexander Mazur

 From:

 Jessica Chu

 CC:

 <noinput>

 Hi Alexander,

 I am writing to provide an update for Project Alpha.

 <...>

 As for the deadline, we are still on track to complete the project by the end of Q2 (on or before June 30th, 2023).

 <noinput>
 A> The project's deadline is still on track, as confirmed in the email, with the project being scheduled for completion by the end of Q2, specifically on or before June 30th, 2023.


 70% 70/100 [08:23<03:12,  6.41s/it]INFO 2024-06-26 20:59:15,282 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Identify the order status based on the email content to understand the package delivery.
 I> Subject: Order #82720: Your Order with Model PX100 Has Shipped

 Date:

 Tuesday, December 7, 2021 at 2:34:53 PM Eastern Standard Time

 From:

 Amazon Customer Service

 To:

 James Dunn

 Hi James,

 We have good news! Your order #82720 with Model PX100 has been shipped. You can track your package with this link:

 ...

 Shipped Items
 -----------

 Model PX100 - Order #82720
 A> The order status indicated in the email is "shipped."

 Q> Name the attachments to provide more context or help organize them based on the information in the email.
 I> 
 A> Based on the context, the attachments could be named as "2022 Semi-Annual Operating Budget Plan" and "Q2 Expense Overview."


 72% 72/100 [08:33<02:50,  6.09s/it]INFO 2024-06-26 20:59:26,154 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Who is the recipient of the email and what is their role?
 I> Subject: Meeting Reminder

 Date:

 Tuesday, March 12, 2024 at 9:12:50 AM Central Standard Time

 From:

 Gary Butterfield

 To:

 Don Boccaccio

 Don,

 I'm just following up regarding our meeting on Friday, March 15, 2024. As previously discussed, we will be discussing the details of the project and its scope.

 Best,

 Gary
 A> The recipient of the email is Don Boccaccio and their role is implied to be a stakeholder or participant in the meeting since their name is in the 'To' field.

 Q> Can you summarize the main request or actionable item from the email in 1-2 sentences?
 I> Subject: Document Update

 Date:

 Monday, March 3, 2025 at 11:34:19 AM Mountain Standard Time

 From:

 Bob Arnot

 To:

 Monica Allgeier

 CC:

 David Slot

 Hi Monica,

 Hope you are doing well. I wanted to reach out about the document we have been working on. I believe there are a few sections that need more clarity in order to be fully aligned with the scope of the project. Specifically, section 3.2 regarding "System Components" needs some further details.

 In addition, we should consider updating the illustrations in Appendix A to be more consistent with our latest design guidelines. I have some initial thoughts on this but would like to get your feedback before making any changes.

 Best,

 Bob
 A> The main request from the email is to update the clarity of section 3.2 about "System Components" and consider updating the illustrations in Appendix A to be consistent with the latest design guidelines.


 74% 74/100 [08:46<02:41,  6.20s/it]INFO 2024-06-26 20:59:39,037 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Explain the primary change in the requested document and its reason in the given email example.
 I> Subject: Parental Leave Policy Update

 Date:

 Tuesday, August 23, 2022 at 5:15:56 PM EDT

 To:

 Human Resources Team

 From:

 Benjamin Stillwater

 CC:

 <noinput>

 Hi HR Team,

 I am writing to propose an update to the Parental Leave Policy. I have attached the updated policy with the proposed changes.

 The primary change is an increase in the fully paid parental leave duration from 8 weeks to 12 weeks, to better align with our competitors' offering and improve recruitment efforts.

 Based on recent staff feedback, I also modified the policy to allow both primary and secondary caregivers to use the 12 weeks fully paid parental leave.

 Kindly review this revised policy and let me know if this meets your expectations.

 Best regards,

 Benjamin Stillwater

 Director of People Operations
 A> The primary change in the requested document is an increase in fully paid parental leave duration from 8 weeks to 12 weeks and extending the use of the 12 weeks fully paid parental leave for both primary and secondary caregivers. The reason for this change is better alignment with competitors' offerings and aiming to improve recruitment efforts and cater to staff feedback.

 Q> Summarize the overall tone conveyed by the sender in the email.
 I> Subject: Feedback Request: Widget Design

 Date:

 Wednesday, October 20, 2021 at 10:06:28 AM EDT

 To:

 Nancy Lambert

 From:

 Craig Spencer

 CC:

 <noinput>

 Dear Nancy,

 I hope you are doing well. I recently came across your widget design, and I would like to express my appreciation for the creativity and detailed approach. The design is nicely done and includes thoughtful functionality for end-users.

 However, I noticed there is room for improvement with regards to responsiveness on tablet devices. I took the liberty of testing the responsiveness, and I found a few issues. I have attached a revised design with marked changes and a brief description of the enhancements.

 Overall, I genuinely enjoyed your work and believe with minor adjustments, it will be a great success in the market.

 Warm regards,

 Craig Spencer

 Product Manager
 A> The overall tone conveyed by the sender (Craig Spencer) is generally positive and appreciative; while also offering constructive feedback on the widget design, expressing confidence that the design will succeed with minor adjustments.


 76% 76/100 [09:01<02:37,  6.57s/it]INFO 2024-06-26 20:59:53,800 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the main topic of the provided email discussing the sales report?
 I> Subject: Sales Report for Q3 2021

 Date:

 Friday, October 1, 2021 at 10:15:00 AM EDT

 From:

 Sales Department

 To:

 Management Team

 CC:

 <noinput>

 Dear Management Team,

 Please find the attached sales report for Q3, featuring the following insights:

 * Region-wise sales performance with in-depth analysis
 * Comparison with Q2 sales figures (with percentage changes)
 * Identification of top-performing and underperforming sales personnel
 * Product-wise sales performance and recommendations

 Kindly review the attached report and reach out if there are any questions.

 Best regards,
 Sales Department
 A> The main topic of the provided email discussing the sales report is the analysis of region-wise sales performance, Q3 vs Q2 comparison, identification of top and underperforming sales personnel, and product-wise sales performance along with recommendations.

 Q> What is the deadline for the progress update requested in this email?
 I> Subject: Project Update: Software Integration

 Date:

 Tuesday, March 15, 2022 at 4:42:00 PM EDT

 From:

 Jane Rawlings

 To:

 Project Team

 CC:

 <noinput>

 Hi Project Team,

 Michael requested a progress update on the software integration project for tomorrow's leadership meeting. Please make sure you send all the necessary info to Jane Rawlings by end of day today (preferably an hour earlier) so she can put together a brief update for Michael.

 Thanks,
 Jane
 A> The deadline for the progress update requested in this email is the end of the day today (preferably an hour earlier).


 78% 78/100 [09:14<02:23,  6.52s/it]INFO 2024-06-26 21:00:06,573 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the issue that the sender is facing, as explained in the email?
 I> Subject: Slow Network Performance

 Date:

 Monday, June 5, 2023 at 2:30:34 PM Eastern Daylight Time

 From:

 Mikaila Young

 To:

 Network Support Team

 CC:

 <noinput>

 Hello Network Support,

 Our team at the Los Angeles branch is facing slow network performance for the past two days. We've tried contacting the local IT but it appears they are also unaware of the issue. We need to identify and rectify the issue as it's negatively affecting our workflow.

 Appreciate your prompt assistance.

 Best regards,

 Mikaila Young

 Business Development Manager
 A> The issue that Mikaila Young, the sender, is facing is slow network performance at the Los Angeles branch for the past two days, which is negatively affecting the team's workflow.

 Q> What is the deadline for the task assigned to the recipient mentioned in the email?
 I> Subject: Approval for Advertising Campaign

 Date:

 Friday, August 18, 2023 at 12:24:01 PM Eastern Standard Time

 From:

 Jonathan Chow

 To:

 Abigail Pierce

 CC:

 <noinput>

 Hi Abigail,

 Hope you're doing well! I have sent over the advertising campaign proposal for your team. I would appreciate if you could go through it and approve the campaign as soon as possible as we need to launch it before the Labor Day weekend.

 Thanks!

 Best,

 Jonathan Chow

 Marketing Manager
 A> The deadline for the task assigned to the recipient, Abigail Pierce, is before the Labor Day weekend.


 80% 80/100 [09:27<02:09,  6.48s/it]INFO 2024-06-26 21:00:19,409 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 INFO 2024-06-26 21:00:23,576 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the approximate arrival date of the Odyssey G7 32-Inch monitors?
 I> Same as above
 A> The estimated arrival date of the Odyssey G7 32-Inch monitors is March 7, 2024.

 Q> Who is the vendor for the Odyssey G55C 27-Inch monitors?
 I> Same as above
 A> The email does not explicitly mention the vendor for the Odyssey G55C 27-Inch monitors. However, it does mention that when a specialist from procurement reviews the request, they determine which supplier to use. Therefore, it is safe to assume that the supplier information can be obtained by the procurement specialist as per the procurement process mentioned in the email.


 82% 82/100 [09:41<02:00,  6.70s/it]INFO 2024-06-26 21:00:33,787 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> To whom is the email sent and who are the others copied in the email?
 I> Subject: Weekly Marketing Team Meeting

 Date:

 Thursday, March 24, 2023 at 3:45:00 PM Eastern Daylight Time

 From:

 Kara Williams

 To:

 Marketing Team

 CC:

 Sarah Steele (Product Manager), Stephen Weathers (Marketing Director)

 <noinput>
 A> The email is sent to the Marketing Team, with Sarah Steele (Product Manager) and Stephen Weathers (Marketing Director) being copied.


 83% 83/100 [09:47<01:51,  6.53s/it]INFO 2024-06-26 21:00:39,552 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the expected completion date for the shock absorber replacements?
 I> Subject: Shock Absorber Replacements

 Date: 

 Tuesday, February 21, 2023 at 9:05:10 AM Eastern Standard Time
 To:

 Casey Contractor
 From:

 James Waldon

 CC:
 <noinput>

 Hi Casey,

 Regarding the order 123456, we are glad to inform you that the shock absorbers have arrived on time. We have started the assembly work. The complete vehicle will be sent for dynamometer testing by next week.

 Thanks,

 James Waldon

 Production Supervisor
 A> The expected completion date for the shock absorber replacements is next week, when the complete vehicle will be sent for dynamometer testing.

 Q> Who is the sender of the most recent email, and what was the subject line?
 I> 
 A> The sender of the most recent email is James Waldon, and the subject line is 'Shock Absorber Replacements.'


 85% 85/100 [09:58<01:32,  6.18s/it]INFO 2024-06-26 21:00:50,506 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the request being made in the email related to the handling of the damaged server?
 I> Subject: Urgent Attention Required - Damaged Server

 Date:

 Wednesday, February 20, 2024 at 8:55:00 AM Eastern Standard Time

 From:

 Herb Hull

 To:

 Pauline Armitage

 Hi Pauline,

 I regret to inform you that the server we received last week was damaged during the delivery process. Unfortunately, this means that we cannot use it for the time being.

 Could you please arrange for the repair or replacement as soon as possible, and confirm the earliest possible time frame for resolution?

 Best,

 Herb Hull
 A> The email is requesting that the damaged server be repaired or replaced as soon as possible, and is asking for confirmation of the earliest possible time frame for resolution.

 Q> What is the location of the meeting mentioned in the email, and at what time was it scheduled?
 I> Subject: Weekly Project Team Meeting

 Date:

 Monday, March 25, 2024 at 4:32:00 PM Eastern Standard Time

 From:

 Gillian Hart

 To:

 Jeremy Plank

 Cc:

 Project Team Members

 Hi Jeremy,

 As previously discussed, the Weekly Project Team Meeting has been scheduled for this coming Thursday at 10:00 AM at the main conference room on the 12th floor.

 Best,

 Gillian
 A> The location of the meeting mentioned in the email is at the main conference room on the 12th floor, and it was scheduled for 10:00 AM.


 87% 87/100 [10:10<01:20,  6.18s/it]INFO 2024-06-26 21:01:02,865 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the date, time, and timezone of the scheduled meeting in the email?
 I> Subject: Team Project Meeting

 Date:

 Tuesday, November 15, 2022 at 10:00:00 AM Eastern Standard Time

 From:

 Samuel Johnson

 To:

 <noinput>

 CC:

 Team Members

 <noinput>
 A> The date of the scheduled meeting in the email is Tuesday, November 15, 2022 at 10:00:00 AM Eastern Standard Time.

 Q> What is the biggest challenge mentioned by the manager Jason regarding the ongoing project in the email?
 I> Subject: Project Update and Challenges

 Date:

 Wednesday, May 3, 2023 at 4:30:00 PM Eastern Daylight Time

 From:

 Jason Paul (Project Manager)

 To:

 Project Team

 CC:

 <noinput>
 A> The biggest challenge mentioned by Jason regarding the ongoing project is the increased competition from a new market entrant and a limited budget for the marketing campaign.


 89% 89/100 [10:21<01:05,  5.99s/it]INFO 2024-06-26 21:01:14,038 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What modifications are required for the sales proposal, as discussed in the email?
 I> Subject: Revisions for Sales Proposal

 Date:

 Monday, April 10, 2023 at 1:45:16 PM Eastern Standard Time
 From:

 Maryam Azizi
 To:

 Team Members
 CC:

 <noinput>

 Hi Team,

 After review, I found a few sections in the sales proposal that could use improvement.

 1. Strengthen our company's credentials to demonstrate our expertise in the field.
 2. Add more details on product features and their benefits.
 3. Rebalance the text and visuals to better engage the potential clients.

 Let's make these updates by EOD Thursday.

 Best,
 Maryam
 <noinput>
 A> Three modifications should be applied to the sales proposal as mentioned in the email. First, enhance the company's credentials to showcase domain expertise. Second, include more details about the product features and their benefits. Lastly, achieve a better balance between text and visuals for higher viewer engagement. All these improvements should be completed by the end of the day on Thursday.

 Q> What are the three options provided regarding the subscription plan issue, and who suggested them?
 I> Subject: Subscription Plan Solutions

 Date:

 Tuesday, May 2, 2023 at 10:10:23 AM Eastern Standard Time
 From:

 <noinput>
 To:

 <noinput>
 CC:

 Kim Hsiao

 Hi everyone,

 As we discussed last week, I've come up with three possible solutions to the subscription plan issue:

 1. A cheaper, limited plan
 2. A pro plan that includes advanced features
 3. Pricing discounts for annual subscriptions

 Let me know what you think!

 Best,
 Kim
 <noinput>
 A> Kim has provided three options for the subscription plan issue, which include: a cheaper, limited plan; a pro plan featuring advanced features; and annual subscription pricing discounts.


 91% 91/100 [10:34<00:55,  6.17s/it]INFO 2024-06-26 21:01:27,161 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What is the deadline for completing the report as mentioned in the email?
 I> Subject: Project Completion and Next Steps

 Date:

 Friday, June 4, 2021 at 10:38:25 AM Eastern Standard Time

 From:

 Lucy Corporate

 To:

 Team Members

 Greetings Team,

 I hope this email finds you well. I am pleased to announce that the current project has been successfully completed. Great job!

 Please wrap up the final steps and have the final report ready for submission by end of the day on June 10.

 Best,

 Lucy Corporate
 A> The deadline for completing the report is end of the day on June 10, as mentioned in the email.

 Q> What is the main reason for the cancellation of the conference as mentioned in the email?
 I> Subject: Conference Cancellation Notice

 Date:

 Friday, July 16, 2021 at 9:49:21 AM Eastern Standard Time

 From:

 Monica Johnson

 To:

 Conference Participants

 Dear Conference Participants,

 Regrettably, we need to inform you that the upcoming conference has been cancelled due to unforeseen circumstances beyond our control.

 We apologize for any inconvenience this may cause and sincerely regret the inconvenience this decision might create.

 Best Regards,

 Monica Johnson
 A> The conference has been cancelled due to unforeseen circumstances beyond the organizer's control, as mentioned in the email.


 93% 93/100 [10:46<00:42,  6.08s/it]INFO 2024-06-26 21:01:38,944 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> What payment method is specified in the email for the "January Invoices"?
 I> Subject: January Invoices

 Date: 

 Friday, February 3, 2023 at 11:12:59 PM Eastern Standard Time
 To:

 Jake Stanton

 From:

 Eva Green

 CC:
 <noinput>

 Dear Jake,

 Happy Friday! I wanted to go ahead and send you over the January invoices. This time around, we've decided to switch to ACH payments, as this method has proven to be faster and more convenient for us.

 You're all set to make the ACH payment. If you have any questions about this change, just let me know.

 Best,

 Eva Green

 Accounts Receivable
 A> The payment method specified in the email for the "January Invoices" is ACH payments.

 Q> What are the key changes in the "Project Scope Statement" update mentioned in the email?
 I> Subject: Project Scope Statement Update

 Date: 

 Thursday, February 23, 2023 at 11:45:34 AM Pacific Standard Time
 To:

 Anthony Shultz

 From:

 Kristin Schneider

 CC:
 <noinput>

 Hi Anthony,

 I've updated the "Project Scope Statement" to include two new features requested by the marketing department:

 1. A customer review section on the website.
 2. An email notification system to remind users when a new feature is available.

 Please have a look and let me know if you have any questions.

 Best,

 Kristin Schneider

 Project Manager
 A> The key changes in the "Project Scope Statement" update mentioned in the email are the inclusion of a customer review section on the website and an email notification system to remind users when a new feature is available.


 95% 95/100 [10:59<00:30,  6.19s/it]INFO 2024-06-26 21:01:51,826 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Who will be the presenter for the monthly IT meeting and what is the main topic?
 I> Subject: Monthly IT Meeting: February 16, 2023

 Date:

 Thursday, January 26, 2023 at 1:47:22 PM Eastern Standard Time

 From:

 Avery Jenkins

 To:

 IT Team

 Hi All,

 I'd like to inform you that our colleague, Raul Cortez, will be presenting a topic on AI-enabled cybersecurity tools at the IT meeting on Thursday, February 16, 2023.

 Avery
 A> Raul Cortez will be the presenter for the monthly IT meeting on February 16, 2023, and the main topic will be AI-enabled cybersecurity tools, as mentioned in the email.


 96% 96/100 [11:09<00:27,  6.85s/it]INFO 2024-06-26 21:02:01,697 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Can you determine if the client has agreed to the proposed meeting time on Friday at 10:00 am, as mentioned in the email?
 I> Subject: Meeting Proposal

 Date:

 Monday, March 13, 2023 at 10:00:00 AM Eastern Daylight Time

 From:

 Dean Clark

 To:

 Martha Thompson

 CC:
 <noinput>

 Hi Martha,

 Hope this email finds you well. I'd like to propose a meeting to discuss the project details on Friday at 10:00 am. Are you available at that time?

 Looking forward to your response.

 Best,

 Dean Clark

 Project Coordinator
 A> No, the client has not agreed to the proposed meeting time on Friday at 10:00 am. The email is a proposal, and the client has not explicitly confirmed their availability.

 Q> What are the new deadlines for Alex's and Mike's tasks, as specified in the email?
 I> Subject: Task Deadlines Update

 Date:

 September 21, 2023 at 3:47:14 PM EDT

 From:

 Melissa Brown

 To:

 Alex Hayes, Mike Summers

 CC:
 <noinput>

 Dear Alex and Mike,

 Due to a few unforeseen circumstances, we need to adjust the deadlines for your current tasks. Alex, your new deadline is now Thursday, September 28th at 5:00 pm, and Mike, your new deadline is Friday, September 29th at 12:00 pm.

 Best regards,

 Melissa Brown

 Team Leader
 A> The new deadline for Alex's task is Thursday, September 28th at 5:00 pm, and the new deadline for Mike's task is Friday, September 29th at 12:00 pm.


 98% 98/100 [11:22<00:13,  6.70s/it]INFO 2024-06-26 21:02:14,493 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->email->reasoning
 Q> Who is responsible for processing the order for additional office supplies, as mentioned in the email?
 I> Subject: Order Request: Office Supplies

 Date:

 Monday, February 7, 2022 at 9:45:36 AM EST

 From:

 Jessica Pierce

 To:

 Office Manager

 CC:

 <noinput>

 Dear Office Manager,

 As the designated office supplies coordinator, I am reaching out to request additional supplies:

 * 10 boxes of printing paper, white (8.5 x 11 inches)
 * 2 boxes of colored markers, assorted colors
 * 3 packs of adhesive note pads

 Kindly process this request and confirm once the shipment is received.

 Best regards,
 Jessica Pierce

 Office Supplies Coordinator
 A> Jessica Pierce, the designated office supplies coordinator, is responsible for processing the order for additional office supplies, as mentioned in the email.

 Q> Which department(s) is (are) involved in the collaborative project mentioned in this email?
 I> Subject: Urban Development Project Collaboration

 Date:

 Tuesday, June 8, 2021 at 10:30:00 AM CDT

 From:

 Project Coordinator

 To:

 Architecture Team, Engineering Team, Land Use Planning Team

 CC:

 <noinput>

 Dear Architecture, Engineering, and Land Use Planning Teams,

 The Project Coordinator is pleased to announce the start of the Urban Development Project, which requires collaboration between our teams.

 Please coordinate for the following tasks:

 * Architecture Team: Building design and site layout
 * Engineering Team: Construction oversight and execution
 * Land Use Planning Team: Local regulations and permits

 Let's kick off our first meeting this Friday at 9 AM in the large conference room.

 Best regards,
 Project Coordinator
 A> The Architecture Team, the Engineering Team, and the Land Use Planning Team are the departments involved in the collaborative Urban Development Project, as mentioned in the email.


 100% 100/100 [11:35<00:00,  6.65s/it]
 100% 100/100 [11:35<00:00,  6.95s/it]
 INFO 2024-06-26 21:02:27,573 generate_data.py:609: generate_data 100 instructions generated, 13 discarded due to format (see /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/email/reasoning/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T20_50_52.log), 0 discarded due to rouge score
 INFO 2024-06-26 21:02:27,573 generate_data.py:613: generate_data Generation took 695.40s
 Completed 104.5 KiB/227.6 KiB (741.0 KiB/s) with 4 file(s) remaining
 upload: ../outputtopush/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T20_50_52.json to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/email/reasoning/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T20_50_52.json
 Completed 104.5 KiB/227.6 KiB (741.0 KiB/s) with 3 file(s) remaining
 Completed 208.0 KiB/227.6 KiB (1.1 MiB/s) with 3 file(s) remaining  
 upload: ../outputtopush/train_Mixtral-8x7B-Instruct-v0_2024-06-26T20_50_52.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/email/reasoning/train_Mixtral-8x7B-Instruct-v0_2024-06-26T20_50_52.jsonl
 Completed 208.0 KiB/227.6 KiB (1.1 MiB/s) with 2 file(s) remaining
 Completed 219.2 KiB/227.6 KiB (899.7 KiB/s) with 2 file(s) remaining
 upload: ../outputtopush/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T20_50_52.log to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/email/reasoning/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T20_50_52.log
 Completed 219.2 KiB/227.6 KiB (899.7 KiB/s) with 1 file(s) remaining
 Completed 227.6 KiB/227.6 KiB (755.6 KiB/s) with 1 file(s) remaining
 upload: ../outputtopush/test_Mixtral-8x7B-Instruct-v0_2024-06-26T20_50_52.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/email/reasoning/test_Mixtral-8x7B-Instruct-v0_2024-06-26T20_50_52.jsonl
 compositional_skills/writing/freeform/social_media/twitter/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/writing/freeform/social_media/twitter/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/writing/freeform/social_media/twitter --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T21:02:30Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/writing/freeform/social_media/twitter/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 21:02:38,922 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->social_media->twitter
 [31mGenerating dataset failed with the following error: There was a problem with the new data, please make sure the yaml is formatted correctly, and there is enough new data(2+ Q&A))[0m

  0% 0/100 [00:00<?, ?it/s]
 compositional_skills/writing/freeform/grammar/basic_grammer_tests/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/writing/freeform/grammar/basic_grammer_tests/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/writing/freeform/grammar/basic_grammer_tests --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T21:02:39Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/writing/freeform/grammar/basic_grammer_tests/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 21:02:48,649 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the spelling mistake in this sentence: "The crab was grumpy because it's claw was pinched."
 I> The crab was grumpy because it's claw was pinched.
 A> The crab was grumpy because its claw was pinched.

 Q> Transform this sentence into interrogative form: "You are going to the concert tonight."
 I> You are going to the concert tonight.
 A> Are you going to the concert tonight?


  2% 2/100 [00:08<07:18,  4.47s/it]INFO 2024-06-26 21:02:57,595 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:02:58,856 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:00,070 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:01,412 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:02,640 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:03,933 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the spelling of this sentence: "I am going to the skool."
 I> I am going to the skool.
 A> I am going to the school.

 Q> Identify the verb in this sentence: "The sun sets in the west."
 I> The sun sets in the west.
 A> The verb in this sentence is "sets".


  4% 4/100 [00:23<10:01,  6.26s/it]INFO 2024-06-26 21:03:12,619 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:13,992 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:15,273 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct this sentence: "I enjoys playing soccer."
 I> I enjoys playing soccer.
 A> I enjoy playing soccer.

 Q> Find the subject in this sentence: "The sun rises in the east."
 I> The sun rises in the east.
 A> The subject of the sentence "The sun rises in the east." is "The sun".


  6% 6/100 [00:35<09:28,  6.05s/it]INFO 2024-06-26 21:03:24,210 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:26,765 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:28,326 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:29,918 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:31,012 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:32,520 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:33,935 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:35,155 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:36,549 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Which word in the sentence is used as an adjective: "The quick brown fox jumps over the lazy dog."
 I> The quick brown fox jumps over the lazy dog.
 A> The word "quick" is used as an adjective.

 Q> Combine these two sentences using a conjunction: "She went to the store. She bought a soda."
 I> She went to the store. She bought a soda.
 A> She went to the store and she bought a soda.


  8% 8/100 [00:57<12:07,  7.91s/it]INFO 2024-06-26 21:03:45,722 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:47,094 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:48,483 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:49,809 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:51,210 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:03:52,397 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Change the sentence into past tense: "I read the book yesterday."
 I> I read the book yesterday.
 A> I read the book yesterday. (Note: The sentence is already in the past tense)

 Q> Fill in the blank with the appropriate form of the verb: "The sun \_\_\_\_\__ shining brightly today."
 I> The sun <noinput> shining brightly today.
 A> The sun is shining brightly today.


 10% 10/100 [01:13<11:58,  7.98s/it]INFO 2024-06-26 21:04:01,935 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:04:03,229 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:04:04,636 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the subject-verb agreement in this sentence: "The dogs barks at the mailman."
 I> The dogs barks at the mailman.
 A> The correct sentence is "The dogs bark at the mailman."

 Q> Identify the noun in this sentence: "She gives her brother a book for his birthday."
 I> She gives her brother a book for his birthday.
 A> The noun in the sentence is "book."


 12% 12/100 [01:25<10:43,  7.31s/it]INFO 2024-06-26 21:04:13,954 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:04:15,666 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:04:16,960 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:04:18,001 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:04:19,293 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:04:20,846 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:04:22,120 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Provide the correct verb tense for the given sentence: "I \_\_\_\_ to school yesterday." (choose between goes, went, and will go)
 I> 
 A> The correct verb tense is "went."

 Q> Correct the spelling mistakes in this phrase: "that cat is the prettist one around here."
 I> that cat is the prettist one around here
 A> The correct spelling is "that cat is the prettiest one around here."


 14% 14/100 [01:42<11:10,  7.80s/it]INFO 2024-06-26 21:04:31,558 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:04:32,878 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:04:34,198 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:04:35,335 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> What is the past tense of the verb "run"?
 I> 
 A> The past tense of the verb "run" is "ran".

 Q> Rewrite this sentence using the passive voice: "Someone will paint the room tomorrow."
 I> Someone will paint the room tomorrow.
 A> The room will be painted tomorrow.


 16% 16/100 [01:55<10:11,  7.28s/it]INFO 2024-06-26 21:04:43,897 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:04:45,211 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:04:46,333 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the subject-verb agreement error: "The books on the shelf needs dusting."
 I> The books on the shelf <noinput>.
 A> The books on the shelf need dusting.

 Q> Convert the sentence into a question: "She is reading a book."
 I> She is reading a book <noinput>.
 A> Is she reading a book?


 18% 18/100 [02:06<09:11,  6.73s/it]INFO 2024-06-26 21:04:54,914 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Change the verb tense of this sentence to past tense: "I walk in the park every day."
 I> I walk in the park every day.
 A> I walked in the park every day.

 Q> Find the subject-verb agreement error in this sentence: "The dogs barks at the mailman every day."
 I> The dogs barks at the mailman every day.
 A> The correct sentence is "The dogs bark at the mailman every day."


 20% 20/100 [02:15<08:00,  6.01s/it]INFO 2024-06-26 21:05:03,736 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:05:05,304 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:05:06,578 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the punctuation errors in the following sentence: "my sister likes to read shes always been a reader"
 I> 
 A> "My sister likes to read; she's always been a reader."


 21% 21/100 [02:26<09:13,  7.00s/it]INFO 2024-06-26 21:05:15,244 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:05:16,674 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> What is the verb in this sentence: "The children will be playing in the park tomorrow"?
 I> 
 A> The verb in the sentence is "playing."

 Q> Add the correct punctuation at the end of this sentence: "The cat sat on the mat and purred for a long time"
 I> The cat sat on the mat and purred for a long time
 A> The cat sat on the mat and purred for a long time.


 23% 23/100 [02:36<08:09,  6.36s/it]INFO 2024-06-26 21:05:25,477 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:05:26,823 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:05:28,277 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:05:29,710 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:05:30,924 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:05:32,418 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:05:33,748 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:05:35,019 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:05:36,351 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:05:37,580 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:05:39,149 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Change the incorrect capitalization in this sentence: "My friendS and i are going to the park."
 I> My friendS and i are going to the park.
 A> My friends and I are going to the park.

 Q> Modify the sentence to include a fragment: "I have a lot of work. Also the concert starts at 7."
 I> 
 A> One example of a sentence with a fragment added could be "I have a lot of work. Additionally, the concert starts at 7."


 25% 25/100 [02:59<09:59,  8.00s/it]INFO 2024-06-26 21:05:48,209 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:05:49,827 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:05:51,033 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the spelling error in this sentence: "There whas a cat siting on the fence."
 I> There whas a cat siting on the fence.
 A> The correct spelling is: "There was a cat sitting on the fence."

 Q> Change this sentence to passive voice: "The company will launch the new product next week."
 I> The company will launch the new product next week.
 A> The new product is going to be launched by the company next week.


 27% 27/100 [03:11<08:52,  7.29s/it]INFO 2024-06-26 21:05:59,743 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:06:01,189 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:06:02,846 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:06:04,029 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the spelling mistakes in this sentence: "The car needs a good wash, it is full of durt."
 I> The car needs a good wash, it is full of durt.
 A> The correct sentence is: "The car needs a good wash, it is full of dirt."

 Q> Identify the proper noun in this sentence: "New York City is a popular tourist destination."
 I> New York City is a popular tourist destination.
 A> The proper noun is "New York City."


 29% 29/100 [03:24<08:21,  7.07s/it]INFO 2024-06-26 21:06:12,939 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:06:14,336 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Combine these two sentences into one using a relative clause: "The musician. He played a beautiful melody. The audience clapped loudly."
 I> 
 A> The musician, who played a beautiful melody, received loud applause from the audience.

 Q> What is the verb in this sentence: "The kangaroos in the park are always hopping and bouncing."
 I> 
 A> The verb in the sentence is "are hopping and bouncing."


 31% 31/100 [03:34<07:26,  6.47s/it]INFO 2024-06-26 21:06:23,167 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:06:24,355 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Change the verb tense from past to present in this sentence: "She visited her family last weekend."
 I> She visited her family last weekend.
 A> She visits her family every weekend.

 Q> Combine these two sentences into one using a relative pronoun: "She walked along the beach. She picked up a seashell."
 I> She walked along the beach. She picked up a seashell.
 A> She walked along the beach and picked up a seashell.


 33% 33/100 [03:44<06:42,  6.00s/it]INFO 2024-06-26 21:06:33,075 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:06:34,256 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Change the verb tense to past tens in the given sentence: "She reads a book."
 I> She reads a book.
 A> She read a book.

 Q> Revise the sentence using a pronoun: "The dog, it wagged its tail, and greeted the boy warmly."
 I> 
 A> It wagged its tail and greeted the boy warmly, the dog.


 35% 35/100 [03:54<06:09,  5.68s/it]INFO 2024-06-26 21:06:42,954 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:06:45,009 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:06:46,380 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the spelling mistake in this sentence: "The catt is on the mat."
 I> 
 A> The correct spelling is "The cat is on the mat."

 Q> Identify the subject and predicate of this sentence: "The dog barked loudly."
 I> The dog barked loudly.
 A> The subject of the sentence is "The dog" and the predicate is "barked loudly."


 37% 37/100 [04:06<06:05,  5.81s/it]INFO 2024-06-26 21:06:55,154 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the sentence with the incorrect verb tense: "Yesterday, she watch a movie."
 I> Yesterday, she watch a movie.
 A> Yesterday, she watched a movie.

 Q> Form a question by adding a question mark and inverting the subject and auxiliary verb in the following statement: "She is writing."
 I> She is writing.
 A> Is she writing?


 39% 39/100 [04:15<05:26,  5.36s/it]INFO 2024-06-26 21:07:03,792 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Replace the coordinating conjunction "and" with a semicolon in this sentence: "The dog ran down the street and barked at the mailman."
 I> The dog ran down the street and barked at the mailman.
 A> The dog ran down the street; barked at the mailman.

 Q> Combine these two sentences into one using a relative pronoun: "The child lost his toy. He is looking for it."
 I> The child lost his toy. He is looking for it.
 A> The child who lost his toy is looking for it.


 41% 41/100 [04:24<05:01,  5.11s/it]INFO 2024-06-26 21:07:12,849 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:07:14,138 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:07:15,423 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the following sentence: "She don't like spinach."
 I> She don't like spinach.
 A> The correct sentence is: "She doesn't like spinach."

 Q> Replace the coordinate conjunction "and" with "or" in this sentence: "I want to eat apples and bananas."
 I> I want to eat apples and bananas.
 A> The resulting sentence is: "I want to eat apples or bananas."


 43% 43/100 [04:35<05:01,  5.29s/it]INFO 2024-06-26 21:07:24,276 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Change the sentence to the past tense: "She reads a book in the garden."
 I> 
 A> She read a book in the garden.


 44% 44/100 [04:44<05:28,  5.86s/it]INFO 2024-06-26 21:07:32,784 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:07:33,942 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Combine the two sentences with a coordinating conjunction: "The report is due Friday. Bob will present the findings."
 I> 
 A> A coordinating conjunction such as "and" or "but" can be used to combine the sentences as follows: "The report is due Friday, and Bob will present the findings."

 Q> Provide a subject for this sentence: "Has read the entire book in a day."
 I> 
 A> An example of a sentence with a subject added is: "My little cousin has read the entire book in a day."


 46% 46/100 [04:54<05:02,  5.59s/it]INFO 2024-06-26 21:07:42,923 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:07:44,302 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Change the verb tense in this sentence from past to present: "She walked to the park yesterday."
 I> She walked to the park yesterday.
 A> The changed sentence is "She walks to the park today."

 Q> Identify the subject and verb in this sentence: "A beautifully sung melody filled the air."
 I> A beautifully sung melody filled the air.
 A> The subject is "a beautifully sung melody" and the verb is "filled."


 48% 48/100 [05:04<04:42,  5.43s/it]INFO 2024-06-26 21:07:53,086 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:07:54,208 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:07:55,420 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:07:56,605 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:07:57,941 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:07:59,048 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:00,423 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the following run-on sentence: "I really like to hike it's so peaceful I can think there I feel free."
 I> 
 A> A corrected version of the run-on sentence is: "I really like to hike. It's so peaceful; I can think there. I feel free."

 Q> What is the plural form of the word "child"?
 I> 
 A> The plural form of the word "child" is "children".


 50% 50/100 [05:20<05:12,  6.25s/it]INFO 2024-06-26 21:08:09,165 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:10,450 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:11,942 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:13,282 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:14,659 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the spelling errors in the sentence: "I am gowing to the store to purchace some eggs."
 I> I am gowing to the store to purchace some eggs.
 A> I am going to the store to purchase some eggs.

 Q> Insert an appropriate punctuation mark: The dog not only ran fast but ook the lead in the race.
 I> 
 A> The dog not only ran fast, but took the lead in the race.


 52% 52/100 [05:34<05:13,  6.52s/it]INFO 2024-06-26 21:08:23,388 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Add appropriate punctuation to this sentence: "I live in new york I am a software engineer."
 I> I live in new york I am a software engineer <noinput>.
 A> I live in New York. I am a software engineer.

 Q> Combine these sentences using proper conjunction: "She is a doctor. She helps people in her community."
 I> She is a doctor. <noinput> She helps people in her community.
 A> She is a doctor who helps people in her community.


 54% 54/100 [05:43<04:29,  5.86s/it]INFO 2024-06-26 21:08:32,142 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:33,413 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:34,866 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:36,061 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:37,489 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:38,828 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:40,070 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:41,398 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:42,573 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:43,930 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:45,454 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:46,909 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the following sentence with a spelling mistake: "The cat sit on the mat."
 I> The cat sit on the mat.
 A> The corrected sentence is "The cat sits on the mat."

 Q> Determine if the following sentence uses the correct subject-verb agreement: "The dogs barks at the mailman."
 I> The dogs barks at the mailman.
 A> No, the sentence does not use the correct subject-verb agreement. It should be "The dogs bark at the mailman."


 56% 56/100 [06:07<05:37,  7.67s/it]INFO 2024-06-26 21:08:55,719 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:57,308 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:58,453 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:08:59,576 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:01,042 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:02,758 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:04,125 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:05,129 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:06,598 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:07,979 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:09,616 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:10,890 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:12,312 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:13,764 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Find and fix the grammatical error in this sentence: "She dont have any books."
 I> She dont have any books.
 A> The corrected sentence is "She doesn't have any books."


 57% 57/100 [06:29<07:27, 10.40s/it]INFO 2024-06-26 21:09:18,631 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:20,188 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:21,736 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:22,936 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:24,836 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Change the sentence to passive voice: "Someone stole my wallet."
 I> **
 Someone stole my wallet.
 A> My wallet was stolen.


 58% 58/100 [06:40<07:21, 10.52s/it]INFO 2024-06-26 21:09:29,592 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:30,957 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Convert this active sentence to passive voice: "A girl is eating an apple."
 I> A girl is eating an apple.
 A> The passive sentence is: "An apple is being eaten by a girl."


 59% 59/100 [06:50<07:06, 10.40s/it]INFO 2024-06-26 21:09:39,588 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:41,012 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:42,549 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:43,784 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:44,964 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:46,505 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:47,745 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:49,003 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:09:50,255 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the spelling mistakes in this sentence: "The gargoyls on the rooftop were frightning."
 I> The gargoyls on the rooftop were frightning.
 A> The gargoyles on the rooftop were frightening.


 60% 60/100 [07:10<08:23, 12.58s/it]INFO 2024-06-26 21:09:58,922 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:10:00,553 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Identify the verb in this sentence: "They laughed and danced all night long."
 I> 
 A> The verb in the sentence is "laughed" and "danced."


 61% 61/100 [07:16<07:09, 11.00s/it]INFO 2024-06-26 21:10:05,417 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:10:06,842 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:10:08,345 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the spelling and grammar errors in this paragraph: "Sience is a vast and intristing field of stidy. It help us understand the world aroud us, from the smalest paritcles to the largst galexies."
 I> 
 A> The correct paragraph should read: "Science is a vast and interesting field of study. It helps us understand the world around us, from the smallest particles to the largest galaxies."

 Q> Provide the past tense of the verb "run."
 I> 
 A> The past tense of the verb "run" is "ran."


 63% 63/100 [07:28<05:27,  8.86s/it]INFO 2024-06-26 21:10:17,309 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Identify the verb that does not agree with its subject in this sentence: "The books needs to be organized."
 I> The books needs to be organized.
 A> The verb that does not agree with its subject is "needs". The correct form should be "The books need to be organized."

 Q> Rewrite this sentence to comply with proper capitalization rules: "did you hear about the new school in town?"
 I> did you hear about the new school in town?
 A> The correct capitalization is "Did you hear about the New School in Town?"


 65% 65/100 [07:37<04:12,  7.21s/it]INFO 2024-06-26 21:10:26,292 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:10:27,499 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:10:28,835 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Change this sentence from passive voice to active voice: "Two tickets were bought by John for the concert."
 I> Two tickets were bought by John for the concert
 A> John bought two tickets for the concert.

 Q> Identify the incorrectly used homophone in this sentence: "Their towels where to big, but to small where there ones across the hall."
 I> 
 A> The incorrectly used homophone in the sentence is "where" in the first part of the sentence. The correct form should be "were."


 67% 67/100 [07:49<03:41,  6.70s/it]INFO 2024-06-26 21:10:37,808 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:10:39,063 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the subject-verb agreement error in this sentence: "The authorities is investigating the matter."
 I> 
 A> The corrected sentence should be: "The authorities are investigating the matter."

 Q> Convert the given plural noun into its singular form: "Children"
 I> 
 A> The singular form of "children" is "child."


 69% 69/100 [07:58<03:08,  6.10s/it]INFO 2024-06-26 21:10:47,583 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Convert this active voice sentence to passive voice: "The company will launch the new product next week."
 I> The company will launch the new product next week.
 A> The new product is going to be launched by the company next week.

 Q> What is the subject-verb agreement error in this sentence: "The staffs at the front desk greets every visitor politely."
 I> 
 A> The subject-verb agreement error is that "staffs" should be "staff". The correct form of the sentence is "The staff at the front desk greets every visitor politely."


 71% 71/100 [08:08<02:42,  5.60s/it]INFO 2024-06-26 21:10:56,717 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Identify the verb and correct its tense in the following sentence: "She don't like it."
 I> She don't like it.
 A> The verb in this sentence is "do like" and its tense needs to be corrected. The corrected sentence should be: "She doesn't like it."

 Q> Add the appropriate article (a, an, or the) in the following sentence: "Elephant is big."
 I> Elephant is big.
 A> The corrected sentence should be: "An elephant is big."


 73% 73/100 [08:17<02:21,  5.25s/it]INFO 2024-06-26 21:11:05,658 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:07,262 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:08,907 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the subject-verb agreement issue in the sentence: "The judges, who are from different countries, often have much different opinions."
 I> 
 A> The judges, who are from different countries, often have much different opinion.

 Q> Replace the run-on sentence with two correct sentences: "She tried to open the box it wouldn't budge she hit it once she heard a click and the box popped open."
 I> 
 A> She tried to open the box. It wouldn't budge. She hit it once, and she heard a click. The box popped open.


 75% 75/100 [08:29<02:18,  5.54s/it]INFO 2024-06-26 21:11:18,059 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Replace the incorrectly used passive voice with active voice: "The ball was thrown by John."
 I> 
 A> An example of the passive voice replaced with the active voice is: "John threw the ball."

 Q> Identify any unnecessary words in the following sentence and remove them: "The cat is sitting on the mat in the corner of the room."
 I> 
 A> A more concise version of the given sentence is: "The cat sits on the mat in the room's corner."


 77% 77/100 [08:38<02:00,  5.22s/it]INFO 2024-06-26 21:11:27,065 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:28,538 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:29,886 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:31,446 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:32,934 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Change the plural subject "apples" to singular: "Apples are my favorite fruit."
 I> 
 A> The corrected sentence is: "An apple is my favorite fruit."

 Q> Combine the sentences "She arrived at the hotel last night. She checked into room 2450."
 I> 
 A> The combined sentences are: "She arrived at the hotel last night and checked into room 2450."


 79% 79/100 [08:52<02:02,  5.85s/it]INFO 2024-06-26 21:11:41,610 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:43,115 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:44,755 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:46,488 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:47,865 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:48,993 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:50,235 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:51,483 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:52,784 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:54,824 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:56,224 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:57,506 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:11:59,127 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:00,420 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:01,835 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:03,054 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:04,265 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:05,539 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:06,670 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:07,861 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:08,930 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:10,371 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:11,897 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Replace the incorrect usage with the proper word: "I could of went there yesterday, but decided not to."
 I> 
 A> The correct usage is: "I could have gone there yesterday, but decided not to."

 Q> Change the sentence voice to passive: "The cat chased the mouse around the room."
 I> 
 A> The passive voice sentence would be: "The mouse was chased around the room by the cat."


 81% 81/100 [09:31<03:09, 10.00s/it]INFO 2024-06-26 21:12:20,645 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:21,918 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the spelling error in the sentence: "The cat sit on the mat."
 I> The cat sit on the mat.
 A> The correct spelling is: "The cat sits on the mat."

 Q> Identify the part of speech of the word "run": "I want to run in the park."
 I> I want to run in the park.
 A> The word "run" is a verb in this context.


 83% 83/100 [09:41<02:24,  8.47s/it]INFO 2024-06-26 21:12:30,551 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:32,209 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:33,968 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the spelling error in this sentence: "The teachet is nice."
 I> 
 A> The correct spelling is "The teacher is nice."

 Q> Rewrite the sentence, making sure it has a clear and direct meaning: "Eating food is something that Jamie has an affinity for."
 I> Eating food is something that Jamie has an affinity for.
 A> Jamie enjoys eating.


 85% 85/100 [09:53<01:56,  7.74s/it]INFO 2024-06-26 21:12:42,651 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:44,251 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the misspelled word in this sentence: "The cat sit on the mat."
 I> The cat sit on the mat <noinput>.
 A> The cat sits on the mat.

 Q> Identify the verb in this sentence: "The sun rises in the east."
 I> The sun rises in the east <noinput>.
 A> The verb in the sentence is "rises."


 87% 87/100 [10:04<01:30,  6.93s/it]INFO 2024-06-26 21:12:52,748 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:53,879 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:55,229 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:56,884 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:12:58,119 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> What is the subject-verb agreement for the following sentence? "The books on the shelf needs dusting."
 I> 
 A> The subject-verb agreement for the sentence is incorrect. "Books" is plural, so the verb should be "need" instead of "needs."


 88% 88/100 [10:18<01:39,  8.26s/it]INFO 2024-06-26 21:13:07,171 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:13:08,593 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:13:09,644 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:13:11,269 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Revise this sentence to make it grammatically correct and clear: "I loves to play soccer."
 I> 
 A> The revised sentence should be: "I love to play soccer."

 Q> Form a possessive noun for the singular noun "cat."
 I> 
 A> The possessive form of "cat" is "cat's."


 90% 90/100 [10:31<01:15,  7.60s/it]INFO 2024-06-26 21:13:19,751 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:13:21,434 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:13:22,609 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:13:24,620 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:13:25,890 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Identify the verb tense in the sentence: "She sings beautifully at the concert."
 I> 
 A> The verb tense in the sentence is present tense.

 Q> Rewrite the following sentence using the passive voice: "Someone stole my bike yesterday."
 I> 
 A> A passive voice version of the sentence is: "My bike was stolen yesterday."


 92% 92/100 [10:45<01:00,  7.51s/it]INFO 2024-06-26 21:13:34,381 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> What is the correct use of a hyphen in this compound adjective: "well-known author"?
 I> 
 A> The correct use of a hyphen is "well-known author".

 Q> Combine these two sentences into one sentence using a conjunction: "She came to the party. She was the life of the party."
 I> 
 A> She came to the party and was the life of the party.


 94% 94/100 [10:54<00:38,  6.49s/it]INFO 2024-06-26 21:13:43,010 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:13:44,198 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:13:45,554 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:13:46,844 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the spelling error in this phrase: "Orignialy from New York."
 I> 
 A> The correct spelling is: "Originally from New York."

 Q> Write a sentence using the correct form of the verb "to lie" (meaning to tell an untruth) or "to lay" (meaning to place something down).
 I> 
 A> Examples: "He lies about his past experiences."; "Lay the book on the table."


 96% 96/100 [11:07<00:25,  6.44s/it]INFO 2024-06-26 21:13:55,664 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Correct the spelling errors in this sentence: "I havent seeen that movee lasy yer."
 I> 
 A> I haven't seen that movie lately last year. (Corrected: I haven't seen that movie lately.)

 Q> Change the sentence into interrogative form: "You are preparing dinner for the family."
 I> You are preparing dinner for the family.
 A> Are you preparing dinner for the family?


 98% 98/100 [11:15<00:11,  5.81s/it]INFO 2024-06-26 21:14:04,436 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:05,811 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:07,061 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:08,281 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:09,623 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:11,026 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:12,324 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:13,669 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Provide an example of a simple sentence with a complex subject: "The teacher, along with her students, is going on a field trip tomorrow."
 I> 
 A> A simple sentence with a complex subject is: "The teacher, along with her students, is going on a field trip tomorrow."


 99% 99/100 [11:30<00:07,  7.34s/it]INFO 2024-06-26 21:14:18,757 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:19,968 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:21,178 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:22,337 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:23,737 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:25,154 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:26,319 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:27,712 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:28,779 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 INFO 2024-06-26 21:14:29,916 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->grammar->basic_grammer_tests
 Q> Fill in the blank with the correct word: "She have three beautiful cats."
 I> 
 A> The correct word is "has". The correct sentence is "She has three beautiful cats."

 Q> Rewrite this sentence to eliminate the comma splice: "I went swimming, my sister stayed home."
 I> I went swimming, my sister stayed home.
 A> I went swimming, and my sister stayed home.


 101it [11:49,  8.21s/it]            
 101it [11:49,  7.03s/it]
 INFO 2024-06-26 21:14:38,540 generate_data.py:609: generate_data 101 instructions generated, 354 discarded due to format (see /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/writing/freeform/grammar/basic_grammer_tests/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_02_48.log), 5 discarded due to rouge score
 INFO 2024-06-26 21:14:38,540 generate_data.py:613: generate_data Generation took 709.97s
 Completed 43.2 KiB/198.1 KiB (243.7 KiB/s) with 4 file(s) remaining
 upload: ../outputtopush/train_Mixtral-8x7B-Instruct-v0_2024-06-26T21_02_48.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/writing/freeform/grammar/basic_grammer_tests/train_Mixtral-8x7B-Instruct-v0_2024-06-26T21_02_48.jsonl
 Completed 43.2 KiB/198.1 KiB (243.7 KiB/s) with 3 file(s) remaining
 Completed 44.1 KiB/198.1 KiB (248.0 KiB/s) with 3 file(s) remaining
 upload: ../outputtopush/test_Mixtral-8x7B-Instruct-v0_2024-06-26T21_02_48.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/writing/freeform/grammar/basic_grammer_tests/test_Mixtral-8x7B-Instruct-v0_2024-06-26T21_02_48.jsonl
 Completed 44.1 KiB/198.1 KiB (248.0 KiB/s) with 2 file(s) remaining
 Completed 90.6 KiB/198.1 KiB (506.8 KiB/s) with 2 file(s) remaining
 upload: ../outputtopush/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T21_02_48.json to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/writing/freeform/grammar/basic_grammer_tests/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T21_02_48.json
 Completed 90.6 KiB/198.1 KiB (506.8 KiB/s) with 1 file(s) remaining
 Completed 198.1 KiB/198.1 KiB (782.7 KiB/s) with 1 file(s) remaining
 upload: ../outputtopush/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_02_48.log to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/writing/freeform/grammar/basic_grammer_tests/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_02_48.log
 compositional_skills/writing/grounded/summarization/wiki_insights/concise/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/writing/grounded/summarization/wiki_insights/concise/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/writing/grounded/summarization/wiki_insights/concise --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T21:14:40Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/writing/grounded/summarization/wiki_insights/concise/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 21:14:49,318 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->grounded->summarization->wiki_insights->concise
 [31mGenerating dataset failed with the following error: There was a problem with the new data, please make sure the yaml is formatted correctly, and there is enough new data(2+ Q&A))[0m

  0% 0/100 [00:00<?, ?it/s]
 compositional_skills/extraction/inference/quantitative/asciidoc/tables/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/extraction/inference/quantitative/asciidoc/tables/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/inference/quantitative/asciidoc/tables --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T21:14:50Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/extraction/inference/quantitative/asciidoc/tables/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 21:14:58,753 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables

  0% 0/100 [00:05<?, ?it/s]INFO 2024-06-26 21:15:04,226 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables

  0% 0/100 [00:12<?, ?it/s]INFO 2024-06-26 21:15:11,003 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables

  0% 0/100 [00:18<?, ?it/s]INFO 2024-06-26 21:15:17,155 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables

  0% 0/100 [00:22<?, ?it/s]INFO 2024-06-26 21:15:21,716 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables

  0% 0/100 [00:25<?, ?it/s]INFO 2024-06-26 21:15:24,501 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> How would I insert a header row in an AsciiDoc table, and can you provide an example with five columns of data?
 I> 
 A> Sure! To insert a header row in an AsciiDoc table, just put the header content in the first row, like this:

 .Table with 5 columns
 [%header]
 |===
 |Column 1    | Column 2    | Column 3    | Column 4    | Column 5
 |City       | Population  | State      | Country    | Continent
 |Paris      | 2,140,526   | Ile-de-France | France     | Europe
 |New York    | 8,336,817   | New York    | United States | North America
 |Sao Paulo  | 12,238,454  | Sao Paulo  | Brazil     | South America
 |Tokyo      | 9,530,803   | Tokyo      | Japan      | Asia
 |Sydney     | 5,230,330   | New South Wales | Australia | Australasia
 |===

 Q> Can you create an AsciiDoc table with alternate shading for rows, and include 3 columns of data?
 I> 
 A> Here's the AsciiDoc code for a table with 3 columns of data and alternate row shading:

 .Table with 3 columns and alternate row shading
 [%header, options="header:best-fit;rows:shade"]
 |===
 | Country        | Population   | Area (km sq)
 | United States   | 331,861,000  | 9,147,593
 | Canada         | 38,040,680   | 9,093,507
 | China          | 1,417,329,000 | 9,388,211
 | India          | 1,377,995,000 | 2,973,193
 | Russia         | 146,780,700  | 16,377,742
 | Indonesia      | 276,040,000  | 1,811,570
 | Brazil         | 214,555,000  | 8,456,510
 | Pakistan       | 220,089,000  | 770,875
 | Nigeria        | 210,403,000  | 910,768
 | Bangladesh     | 167,577,000  | 138,573
 | South Africa   | 59,231,000   | 1,214,470
 | Egypt         | 105,739,000  | 997,739
 | Mexico         | 133,787,000  | 1,943,950
 | Philippines     | 110,558,000  | 298,170
 | Morocco        | 36,803,000   | 446,301
 | Peru           | 33,014,000   | 1,279,996
 | Colombia        | 51,136,000   | 1,118,700
 | Vietnam        | 98,723,000   | 311,699
 | Argentina        | 45,441,000   | 2,766,890
 | Algeria         | 44,270,000   | 2,381,740
 |===

 I hope that's helpful! Let me


  2% 2/100 [00:42<13:48,  8.45s/it]INFO 2024-06-26 21:15:41,408 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:15:43,717 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:15:51,057 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Create an Asciidoc table with 5 columns: First Name, Last Name, Title, Email, and Phone Number, with random data for 5 rows.
 I> 
 A> Here's the AsciiDoc code for a table with 5 columns and 5 rows of random data:

 .Table with 5 columns and 5 rows of random data
 [%header, options="header:best-fit;rows:shade"]
 |===
 | First Name | Last Name | Title | Email                     | Phone Number
 | John       | Doe       | Dr.   | [[email protected]](mailto:[email protected])  | +1 (123) 456-7890
 | Jane       | Doe       | Mr.   | [[email protected]](mailto:[email protected])    | +1 (123) 456-7890
 | Michael    | Doe       | Prof. | [[email protected]](mailto:[email protected]) | +1 (123) 456-7890
 | Emily      | Doe       | Ms.   | [[email protected]](mailto:[email protected])    | +1 (123) 456-7890
 | James      | Doe       | Mr.   | [[email protected]](mailto:[email protected])    | +1 (123) 456-7890
 |===

 Q> Show me how to create an Asciidoc table with 2 columns and 5 rows, where the header is centered and shading is applied to every third row.
 I> 
 A> Here's how to create an Asciidoc table with 2 columns and 5 rows, with a centered header, and shading applied to every third row:

 .Table with 2 columns, centered header, and shading on every third row
 [%header, where(rowindex % 3 == 0), options="header:center;rows:shade"]
 |===
 | Column 1 | Column 2
 | First   | Value 1
 | Second  | Value 2
 | Third   | Value 3
 | Fourth  | Value 4
 | Fifth   | Value 5
 |===


  4% 4/100 [01:05<16:24, 10.26s/it]INFO 2024-06-26 21:16:04,452 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:16:12,105 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:16:16,257 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Can you create an AsciiDoc table of popular programming languages sorted by their respective popularity rank?
 I> 
 A> Certainly! Here's the AsciiDoc code for the requested table of popular programming languages sorted by their popularity rank:

 .Table of programming languages sorted by popularity
 [%header, options="header:best-fit"]
 |===
 | Rank | Language       | Average Popularity Score
 | 1    | JavaScript    | 76.592
 | 2    | Python        | 64.201
 | 3    | Java          | 64.002
 | 4    | C#             | 54.513
 | 5    | C++            | 50.835
 | 6    | TypeScript    | 48.484
 | 7    | PHP           | 42.746
 | 8    | Ruby          | 35.471
 | 9    | Swift         | 33.499
 | 10   | Kotlin        | 31.209
 |===

 The data for the table is based on the TIOBE Index for October 2022 which calculates the popularity of programming languages based on the number of search engine hits for programming-related topics.


  5% 5/100 [01:24<20:07, 12.71s/it]INFO 2024-06-26 21:16:23,007 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> What is an exemplary AsciiDoc table format for displaying the top 10 most populous countries based on their estimated 2022 populations?
 I> 
 A> Here's an example AsciiDoc table for displaying the requested data of the top 10 most populous countries based on the estimated 2022 populations:

 .Table of the top 10 most populous countries as of 2022
 [%header, options="header:best-fit"]
 |===
 | Rank | Country          | 2022 Population 
 | 1    | China           | 1,411,000,000 
 | 2    | India           | 1,366,000,000 
 | 3    | United States   | 331,000,000    
 | 4    | Indonesia      | 273,000,000    
 | 5    | Pakistan        | 236,000,000    
 | 6    | Brazil          | 216,000,000    
 | 7    | Nigeria         | 214,000,000    
 | 8    | Bangladesh     | 169,000,000    
 | 9    | Russia          | 142,000,000    
 | 10   | Mexico           | 128,000,000    
 |===

 Please note that all the population numbers listed in this example table are based on the estimated figures of the World Bank and other credible sources.

 Q> How can I create an AsciiDoc table listing the Star Wars characters from the original trilogy along with their respective species and gender?
 I> 
 A> You can create an AsciiDoc table listing the Star Wars characters from the original trilogy along with their respective species and gender as followed:

 .Table of Star Wars characters from original trilogy
 [%header, options="header:best-fit"]
 |===
 | Character               | Species             | Gender        
 |-------------------------|---------------------|---------------|
 | Luke Skywalker          | Human              | Male          
 | Han Solo                | Human              | Male          
 | Leia Organa             | Human              | Female        
 | Vader / Anakin Skywalker | Human              | Male          
 | Yoda                    | Yoda               | Male          
 | Chewbacca               | Wookiee             | Male          
 | Lando Calrissian       | Human              | Male          
 | Emperor Palpatine       | Human              | Male          
 | Boba Fett              | Human (modified)   | Male          
 | Mon Mothma          | Human              | Female        
 |===

 Please note that this table illustratively shows a summary of Star Wars characters from the original trilogy based on the respective species and gender.


  7% 7/100 [01:38<15:49, 10.21s/it]INFO 2024-06-26 21:16:37,485 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:16:41,831 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Can you generate an AsciiDoc table using the given dataset on the most popular Netflix shows, including their titles, seasons, and genres?
 I> | Title              | Seasons | Genre                   |
 |--------------------|---------|-------------------------|
 | Stranger Things    | 4       | Horror/Sci-fi           |
 | The Crown          | 4       | Historical drama       |
 | Narcos             | 3       | Crime/Biography         |
 | The Witcher         | 2       | Fantasy                |
 | The Queen's Gambit | 1       | Drama                  |
 | Mindhunter          | 2       | Crime/Psychology       |
 | The Umbrella Academy| 2       | Superhero/Action        |
 | The Haunting       | 2       | Horror/Anthology        |
 | Master of None     | 3       | Comedy/Drama           |
 | Ozark              | 3       | Crime/Drama             |
 A> Here's the AsciiDoc code for a table with the given dataset of the most popular Netflix shows with their titles, seasons, and genres:

 .Table of popular Netflix shows with their titles, seasons, and genres
 [%header, options="header:best-fit"]
 |===
 | Title                | Seasons | Genre                 |
 |----------------------|---------|-----------------------|
 | Stranger Things      | 4       | Horror/Sci-fi         |
 | The Crown            | 4       | Historical Drama      |
 | Narcos               | 3       | Crime/Biography      |
 | The Witcher           | 2       | Fantasy              |
 | The Queen's Gambit   | 1       | Drama                |
 | Mindhunter           | 2       | Crime/Psychology    |
 | The Umbrella Academy| 2       | Superhero/Action     |
 | The Haunting         | 2       | Horror/Anthology      |
 | Master of None       | 3       | Comedy/Drama         |
 | Ozark                | 3       | Crime/Drama           |
 |===

 This AsciiDoc table is nicely formatted and ready for use.

 Q> Please construct an AsciiDoc table to present data on the most commonly used programming languages, featuring the percentage of developers using each language along with the specific ranking.
 I> 
 A> Here's an example AsciiDoc table for displaying the most commonly used programming languages, featuring their ranking and the percentage of developers using each language:

 .Table of commonly used programming languages and their usage rate
 [%header, options="header:best-fit"]
 |===
 | Rank | Programming Language | % of Developers  
 | 1    | JavaScript         | 65.4%            
 | 2    | Java              | 42.9%            
 | 3    | Python            | 40.5%            
 | 4    | C#                 | 35.6%            
 | 5    | C++                | 32.7%            
 | 6    | TypeScript         | 29.9%            
 | 7    | PHP                | 28.4%            
 | 8    | Ruby              | 12.6%            
 | 9    | Swift             | 10.5%            
 | 10   | Kotlin            | 9.1%             
 |===

 Please note that the numbers are only for reference purposes, and it's not based on any actual survey.


  9% 9/100 [01:58<15:22, 10.13s/it]INFO 2024-06-26 21:16:57,524 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:17:02,076 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Construct a table of all-time international best-selling albums with columns for the title, artist, record label, and sales figures.
 I> 
 A> Here's a sample AsciiDoc table showcasing all-time international best-selling albums with the requested columns:

 .Best-selling albums of all time
 [%header]
 |===
 | Title                       | Artist        | Record Label      | Sales (in millions)
 | Thriller                     | Michael Jackson | Epic Records     | 66
 | Back in Black               | AC/DC          | Atlantic Records   | 50
 | The Dark Side of the Moon  | Pink Floyd    | Harvest/EMI      | 45
 | The Bodyguard (soundtrack)  | Whitney Houston | Arista     | 45
 | Bat Out of Hell               | Meat Loaf      | Epic Records     | 43
 | Their Greatest Hits (1971-1975) | Eagles         | Elektra        | 42
 | Saturday Night Fever (soundtrack) | Bee Gees      | RSO            | 40
 | The Sound of Music (soundtrack) | Julie Andrews   | RCA Victor      | 36
 | Shania Twain              | Up!           | Mercury         | 36
 | Please Hammer, Don't Hurt 'Em | MC Hammer     | Capitol         | 36
 |===

 Q> Present an asciidoc table detailing the last eight Super Bowl winners, consisting of the winning team, their score, the runner-up, their score, and the result date.
 I> 
 A> Here's an AsciiDoc table with the details of the last eight Super Bowl winners, including the winning team and loser, their respective points, along with the result date:

 .Last Eight Super Bowl Champions
 [%header]
 |===
 | Winning Team          | Winning Score | Runner-Up    | Runner-Up Score | Result Date
 | Kansas City Chiefs    | 31           | Philadelphia Eagles   | 20                | Feb 2, 2020
 | New England Patriots   | 13           | Los Angeles Rams | 3              | Feb 3, 2019
 | Philadelphia Eagles   | 41           | New England Patriots  | 33              | Feb 4, 2018
 | New England Patriots   | 34           | Atlanta Falcons    | 28              | Feb 5, 2017
 | Denver Broncos       | 24           | Carolina Panthers   | 10              | Feb 7, 2016
 | New England Patriots   | 28           | Seattle Seahawks   | 24             | Feb 1, 2015
 | Seattle Seahawks     | 43           | Denver Broncos    | 8               | Feb 2, 2014
 | Baltimore Ravens     | 34           | San Francisco 49ers  | 31              | Feb 3, 2013
 |===


 11% 11/100 [02:18<14:47,  9.98s/it]INFO 2024-06-26 21:17:16,945 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Create an AsciiDoc table comparing the battery life, screen size, and camera resolution of the five most popular smartphones in 2022.
 I> 
 A> Here's an example AsciiDoc table that compares battery life, screen size, and camera resolution of the five most popular smartphones in 2022:

 .Comparison of the five most popular smartphones in 2022
 [%header, options="header:best-fit"]
 |===
 | Model        | Battery Life (mAh) | Screen Size (inches) | Camera Resolution (MP)
 | iPhone 14 Pro | 3095             | 6.1                    | 12       
 | Samsung Galaxy S22 Ultra  | 5000         | 6.8                    | 108      
 | Google Pixel 7    | 4355             | 6.4                    | 50       
 | OnePlus 10 Pro | 5000             | 6.7                    | 48       
 | Oppo Find X5 Pro | 4500             | 6.7                    | 50       
 |===

 Please note that the specs listed in this example table are based on preliminary and rumored data as of September 2022 and might be subject to change.

 Q> Generate the AsciiDoc code to create a table outlining the details of the latest Mars rovers.
 I> 
 A> Here's the AsciiDoc code for the table outlining the details of the latest Mars rovers:

 .Table of the latest Mars rovers
 [%header, options="header:best-fit"]
 |===
 | Name         | Launch Date   | Weight (kg)  | Current Status    |
 | Perseverance | Jul 30, 2020 | 1025 kg      | Landed in Jezero Crater, active |
 | Zhurong     | Jul 23, 2020  | 240 kg       | Lands in Utopia Planitia, active |
 | Curiosity  | Nov 26, 2011 | 900 kg       | Active on Mars, exploring Mount Sharp |
 |===

 The data for the table is based on the payload and mission information of NASA and CNSA, the respective space agencies.


 13% 13/100 [02:31<12:46,  8.81s/it]INFO 2024-06-26 21:17:30,034 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:17:35,663 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Create an AsciiDoc table with columns for Project, Start Date, Duration (months), and Completion Date, given the following project information.
 I> * Project: Camera Software Upgrade
 * Start Date: Oct 1, 2021
 * Duration: 4 months
 * Completion Date: Jan 31, 2022
 A> Here's the AsciiDoc code to create a table with the given information:

 .Project management table
 [%header, options="header:best-fit"]
 |===
 |Project                    | Start Date   | Duration (months)  | Completion Date  |
 |Camera Software Upgrade   | Oct 1, 2021    | 4                  | Jan 31, 2022      |
 |===

 Please note that if further projects are given, the AsciiDoc code should be updated accordingly by expanding the table to include an additional row per project.

 Q> Provide an example AsciiDoc code for a table comparing 5 countries' populations and population densities, with an additional column for the continent where each country is located.
 I> 
 A> Here's the AsciiDoc code for a table comparing 5 countries' populations and population densities, with a column for the continent:

 .Country comparison table
 [%header, options="header:best-fit"]
 |===
 | Country      | Population   | Density  | Continent         |
 | Indonesia     | 276,040,000  | 149      | Asia              |
 | Pakistan      | 220,089,000  | 254      | Asia              |
 | Brazil       | 214,555,000  | 23        | America          |
 | Russia       | 146,780,700  | 8.2      | Europe            |
 | Egypt        | 105,739,000  | 103      | Africa            |
 |===


 15% 15/100 [02:49<12:33,  8.87s/it]INFO 2024-06-26 21:17:48,004 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Can you tell me the correct AsciiDoc syntax for a table with merged cells in the header行?
 I> 
 A> Certainly! Merged cells in AsciiDoc headers are achieved through the following syntax:

 .Table with merged header cells
 [%options=header]
 |===
 | | A | B |
 | *Header Row 1* |----+----|
 | Cell 1.1 | Cell 1.2 |
 | Cell 2.1 | Cell 2.2 |
 |===
 In this example, '*Header Row 1*' spans the full width of columns A and B, thus requiring the use of the '----' separator across multiple cells.


 16% 16/100 [02:54<11:31,  8.23s/it]INFO 2024-06-26 21:17:53,488 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:17:59,417 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Create an AsciiDoc table with the information provided about the five most valuable companies in the world based on their 2021 market cap.
 I> | #   | Company            | 2021 Market Cap (USD)       |
 |-----|--------------------|-------------------------------|
 | 1   | Microsoft          | 2,295,093,000,000          |
 | 2   | Apple              | 2,282,892,000,000          |
 | 3   | Amazon             | 1,630,340,000,000          |
 | 4   | Alphabet (Google)   | 1,853,331,000,000          |
 | 5   | Facebook           | 917,412,000,000           |
 A> Use this AsciiDoc code to display the provided information about the five most valuable companies in the world and their 2021 market caps:

 .Table of the five most valuable companies in the world as of 2021
 [%header, options="header:best-fit"]
 |===
 | #   | Company             | 2021 Market Cap (USD)  
 |-----|---------------------|--------------------------
 | 1   | Microsoft           | 2,295,093,000,000        
 | 2   | Apple               | 2,282,892,000,000        
 | 3   | Amazon              | 1,630,340,000,000        
 | 4   | Alphabet (Google)   | 1,853,331,000,000        
 | 5   | Facebook            | 917,412,000,000         
 |===

 This AsciiDoc table provides a clean way to display the most valuable companies in the world with their market caps in 2021.

 Q> Can you craft an AsciiDoc table that demonstrates the five different NATO phonetic alphabet terms and their corresponding words?
 I> 
 A> Here's an example AsciiDoc table with the NATO phonetic alphabet terms and their corresponding words for reference:

 .Table of the NATO phonetic alphabet terms and their corresponding words
 [%header, options="header:best-fit"]
 |===
 | NATO Term  | Corresponding Word |
 |------------|-------------------|
 | Alpha      | Alfa             |
 | Bravo      | Bravo           |
 | Charlie    | Charlie         |
 | Delta      | Delta           |
 | Echo       | Echo            |
 | Foxtrot    | Foxtrot         |
 | Golf       | Golf            |
 | Hotel      | Hotel           |
 | India      | India            |
 | Juliet     | Juliet          |
 | Kilo       | Kilo             |
 | Lima       | Lima             |
 | Mike       | Mike            |
 | November   | November         |
 | Oscar      | Oscar           |
 | Papa       | Papa            |
 | Quebec     | Quebec          |
 | Romeo      | Romeo           |
 | Sierra     | Sierra          |
 | Tango      | Tango           |
 | Uniform    | Uniform         |
 | Victor     | Victor          |
 | Whiskey    | Whiskey         |
 | X-Ray      | X-Ray           |
 | Yankee     | Yankee          |
 | Zulu       | Zulu            |
 |===

 This AsciiDoc table displays the NATO phonetic alphabet terms and their corresponding words for the user's convenience.


 18% 18/100 [03:16<12:38,  9.25s/it]INFO 2024-06-26 21:18:15,744 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Construct an Asciidoc table that lists major programming languages, their respective creators, and the creation date.
 I> 
 A> Here's the AsciiDoc code for the table listing major programming languages and their respective creators and creation dates:

 .Programming languages and their origins
 [%header]
 |===
 | Language     | Creator                | Creation Date  |
 | C             | Dennis Ritchie         | 1972          |
 | C++           | Bjarne Stroustrup      | 1983          |
 | Java          | James Gosling         | 1995          |
 | Python        | Guido van Rossum       | 1991          |
 | JavaScript    | Brendan Eich          | 1995          |
 | R             | Robert Gentleman & Ross Ihaka | 1993          |
 | Swift         | Apple Inc.             | 2014          |
 | Go            | Google                | 2009          |
 |===

 Q> Create an Asciidoc table comparing electric vehicles, their manufacturers, and battery range in miles (EPA rating).
 I> 
 A> Here's the AsciiDoc code for the table comparing electric vehicles, manufacturers, and battery ranges:

 .Electric vehicles' battery ranges (EPA rating)
 [%header, options="header:best-fit"]
 |===
 | Model         | Manufacturer          | Battery Range (miles) |
 | Tesla Model 3 | Tesla                | 263 miles             |
 | Chevrolet Bolt | General Motors      | 259 miles            |
 | Nissan Leaf   | Nissan                | 149 miles             |
 | Hyundai Kona Electric | Hyundai     | 258 miles            |
 | Ford Mustang Mach-E | Ford        | 230 miles            |
 |===

 The data for the table is based on the latest EPA rating information for each electric vehicle.


 20% 20/100 [03:29<11:00,  8.26s/it]INFO 2024-06-26 21:18:28,324 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:18:35,461 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:18:41,250 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Generate an AsciiDoc table for the following list of top-rated programming languages ordered by their popularity and average salaries (in USD).
 I> * Language: Python, JavaScript, Java, C#, C++
 * Popularity: 69%, 71%, 14%, 6%, 5%
 * Average salary: $110,140, $104,204, $103,663, $95,364, $92,704
 A> Here's the AsciiDoc code to create a table with the given information:

 .Popular programming languages and average salaries
 [%header, options="header:best-fit"]
 |===
 | Language   | Popularity (%) | Average Salary (USD)
 | Python     | 69              | $110,140
 | JavaScript  | 71              | $104,204
 | Java       | 14              | $103,663
 | C#         | 6               | $95,364
 | C++        | 5               | $92,704
 |===

 Q> From the given information, create a table displaying the total number of vehicles sold by four major car manufacturers in Q2 2022.
 I> * Manufacturer: Ford, Honda, Toyota, BMW
 * Q2 2022 sold vehicle quantities: 413,567, 332,129, 552,256, 153,432
 A> Here's the AsciiDoc code to create a table with the given information:

 .Total vehicles sold in Q2 2022 by major car manufacturers
 [%header, options="header:best-fit"]
 |===
 | Manufacturer     | Total Vehicles Sold (Q2 2022)
 | Ford             | 413,567
 | Honda            | 332,129
 | Toyota           | 552,256
 | BMW              | 153,432
 |===


 22% 22/100 [03:55<12:40,  9.74s/it]INFO 2024-06-26 21:18:54,036 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Create an Asciidoc table that exhibits the sports, the number of players required for each team, and the popular leagues for each sport.
 I> 
 A> Here's an example AsciiDoc table for sports, players per team, and popular leagues:

 .Popular sports, number of players per team, and popular leagues
 [%header]
 |===
 | Sport          | Players per team | Popular leagues        |
 | Soccer         | 11               | English Premier League, UEFA Champions League |
 | Basketball     | 5                 | NBA, EuroLeague          |
 | American      | 11               | NFL, NCAA Football       |
 | Football       | 11               | NCAA Football, CFL    |
 | Baseball        | 9                 | MLB, NPB                  |
 | Cricket        | 11               | IPL, The Ashes          |
 | Ice Hockey     | 6                 | NHL, KHL                 |
 | Tennis         | 1 (singles)       | Grand Slam, ATP Tour |
 | Volleyball     | 6                 | FIVB, CEV                 |
 | Rugby          | 15               | Six Nations, Rugby World Cup |
 |===

 This table highlights different sports, the number of players needed for each team, and prominent leagues for each sport.

 Q> Can you construct an Asciidoc table from the following information, detailing the notable planets in our Solar System, their sizes, and distances from the Sun?
 I> 
 A> Here's the AsciiDoc code for a table about the Solar System's notable planets and their properties:

 .Notable planets in the Solar System
 [%header, options="header:best-fit"]
 |===
 | Planet   | Size (km)   | Distance from the Sun (AU) |
 | Mercury  | 4,879       | 0.39                      |
 | Venus    | 12,104      | 0.72                      |
 | Earth    | 12,742      | 1.00                      |
 | Mars     | 6,779       | 1.52                      |
 | Jupiter | 139,820     | 5.20                      |
 | Saturn   | 116,460     | 9.58                      |
 | Uranus   | 50,724      | 19.18                     |
 | Neptune  | 49,244      | 30.07                     |
 |===


 24% 24/100 [04:09<11:13,  8.87s/it]INFO 2024-06-26 21:19:07,958 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Explain how to structure an AsciiDoc table for a list of the ten most populous countries and their populations in 2021.
 I> 
 A> Create a table like this in AsciiDoc to display the ten most populous countries and their 2021 populations:

 .Table of the ten most populous countries in 2021
 [%header, options="header:best-fit"]
 |===
 | Rank   | Country            | Population       |
 |--------|--------------------|------------------|
 | 1      | China               | 1,411,000,000    |
 | 2      | India              | 1,366,000,000    |
 | 3      | United States      | 331,000,000      |
 | 4      | Indonesia          | 273,000,000      |
 | 5      | Pakistan           | 230,000,000      |
 | 6      | Brazil             | 214,000,000      |
 | 7      | Nigeria            | 212,000,000      |
 | 8      | Bangladesh        | 165,000,000      |
 | 9      | Russia             | 145,000,000      |
 | 10     | Mexico             | 128,000,000      |
 |===

 This table illustratively shows the ten most populous countries of the world in 2021 based on population numbers.

 Q> Form an AsciiDoc table containing five members from the Marvel Cinematic Universe (MCU) with their respective roles and superpowers.
 I> 
 A> Here's an example of an AsciiDoc table with five members from the Marvel Cinematic Universe and their respective roles and superpowers:

 .Table of five members from the Marvel Cinematic Universe
 [%header, options="header:best-fit"]
 |===
 | Hero               | Role                | Superpowers                      
 |--------------------|--------------------|----------------------------------|
 | Iron Man           | Billionaire Industrialist    | Superhuman intelligence, durability, strength and flight  
 | Captain America   | Super-soldier         | Superhuman speed, strength, durability, and agility |
 | Thor              | God of Thunder       | Superhuman strength, endurance, resistance to injury, and durability, magical powers |
 | Hulk               | Genius / Monster     | Superhuman strength, resistance to physical harm |
 | Black Widow       | Spy                 | Master martial artist, espionage |
 |===

 This AsciiDoc table lists five members from the Marvel Cinematic Universe along with their respective roles and superpowers.


 26% 26/100 [04:23<10:18,  8.36s/it]INFO 2024-06-26 21:19:22,415 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:19:28,829 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:19:32,989 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Extract data from the given AsciiDoc table containing the latest book releases and provide information about the top 3 books with the highest rating.
 I> .Latest Book Releases
 [%header]
 |===
 | Title                  | Author              | Release Date  | Rating |
 | The Pursuit of Happyness      | Chris Gardner       | Jan 3, 2023      | 4.8 |
 | The Great Passage        | Shion Miura         | Feb 6, 2023      | 4.7   |
 | The Four Winds          | Kristin Hannah     | Mar 1, 2023      | 4.5   |
 | Educated              | Tara Westover       | Apr 4, 2023      | 4.6   |
 | Circe                  | Madeline Miller     | May 17, 2023     | 4.7   |
 | Binny's Diwali          | Thrity Umrigar    | Jun 7, 2023      | 4.4   |
 | The Seven ½ Deaths Of Evelyn Hardcastle  | Stuart Turton   | Jul 18, 2023     | 4.6   |
 | Leave The World Behind  | Rumaan Alam        | Aug 4, 2023      | 4.2   |
 |===
 A> The top 3 books with the highest ratings based on the provided AsciiDoc table are:
 1. "The Great Passage" by Shion Miura with a rating of 4.7.
 2. "Circe" by Madeline Miller with a rating of 4.7.
 3. "The Four Winds" by Kristin Hannah with a rating of 4.5.

 Q> Generate an AsciiDoc table that illustrates the top 10 countries by area in descending order.
 I> 
 A> Here's an AsciiDoc table representing the top 10 countries by land area in descending order:

 .Top 10 Countries by Land Area
 [%header]
 |===
 | Rank | Country      | Area (km2)    |
 | 1    | Russia      | 17,098,242    |
 | 2    | Canada      | 9,984,670     |
 | 3    | China       | 9,596,961     |
 | 4    | USA         | 9,833,517     |
 | 5    | Brazil      | 8,516,000     |
 | 6    | Australia   | 7,741,220     |
 | 7    | India       | 3,287,263     |
 | 8    | Argentina    | 2,780,400     |
 | 9    | Kazakhstan  | 2,724,900     |
 | 10   | Algeria     | 2,381,741     |
 |===


 28% 28/100 [04:49<11:37,  9.69s/it]INFO 2024-06-26 21:19:47,779 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Can you help me design an AsciiDoc table comparing the primary features of three different electric vehicles, including their maximum range, battery capacity, and starting price?
 I> 
 A> Certainly! Here's an AsciiDoc table with the primary features of three different electric vehicles:

 .Table of primary features of Electric Vehicles
 [%header, options="header:best-fit"]
 |===
 | Model                        | Maximum Range (miles) | Battery Capacity (kWh) | Starting Price ($)   
 |-----------------------------|----------------------|------------------------|-----------------------
 | Tesla Model S Long Range   | 373                  | 100                   | 79,990               
 | Chevrolet Bolt EUV           | 259                  | 65                    | 33,995                
 | Nissan Leaf Plus             | 226                  | 62                    | 38,200               
 |===

 This table showcases a comparison between the Tesla Model S Long Range, the Chevrolet Bolt EUV, and the Nissan Leaf Plus based on their maximum range, battery capacity, and starting price.

 Q> Generate an AsciiDoc table with the top 10 most populous countries in the world, indicating their populations, areas, and population densities.
 I> 
 A> Here's an AsciiDoc table with the top 10 most populous countries in the world, featuring their populations, areas, and population densities:

 .Table of the most populous countries
 [%header, options="header:best-fit"]
 |===
 | Rank  | Country                   | Population   | Area (km²)    | Population Density 
 |-------|---------------------------|--------------|---------------|--------------------
 | 1     | China                     |1,439,323,776| 9,596,961 | 150              
 | 2     | India                     | 1,380,004,385 | 3,287,263 | 422               
 | 3     | United States             | 331,002,651  | 9,833,517  | 34                
 | 4     | Indonesia                | 273,523,615  | 1,904,569  | 144               
 | 5     | Pakistan                  | 220,892,340  | 881,913    | 251               
 | 6     | Brazil                    | 212,559,417  | 8,515,767  | 25                
 | 7     | Nigeria                   | 206,139,589  | 923,768    | 223               
 | 8     | Bangladesh                | 164,689,383  | 147,570   | 1,116             
 | 9     | Russia                    | 145,934,462  | 17,098,242 | 8.5               
 | 10    | Mexico                    | 128,932,753  | 1,972,550  | 66                
 |===

 Please note that the population and area data are for reference purposes only, and it can vary depending upon the sources.


 30% 30/100 [05:05<10:42,  9.17s/it]INFO 2024-06-26 21:20:03,795 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Showcase the 2021 U.S. federal income tax brackets and rates in an AsciiDoc table with two columns.
 I> 
 A> Present the 2021 U.S. federal income tax brackets and rates in an AsciiDoc table as followed:

 .Table of 2021 U.S. federal income tax brackets and rates
 [%header, options="header:best-fit"]
 |===
 | Taxable Income Range   | Marginal Tax Rate
 |-----------------------|-----------------|
 | $0 - $9,950            | 10%             |
 | $9,951 - $40,525        | 12%             |
 | $40,526 - $86,375      | 22%             |
 | $86,376 - $164,925     | 24%             |
 | $164,926 - $209,425    | 32%             |
 | $209,426 - $523,600    | 35%             |
 | Over $523,600          | 37%             |
 |===

 This AsciiDoc table outlines the 2021 U.S. federal income tax brackets and rates for various taxable income ranges.

 Q> Provide the requested AsciiDoc syntax to display information about five innovative tech companies, including their three-letter acronym, name, and a brief description.
 I> | 3-Letter Acronym (TLA) | Name                        | Brief Description                                                                 |
 |-----------------------|------------------------------|-------------------------------------------------------------------------------------|
 | AIK                   | AI Knights                   | A ground-breaking company building the most advanced artificial intelligence systems.|
 | KGA                   | Kernel Genome Analytics     | A distinguished leader in genome sequencing and bioinformatics                       |
 | GDS                   | Green Development Solutions   | A firm focusing on revolutionizing eco-friendly technologies for sustainable future.|
 | HPG                   | HoloPort Games               | A pioneering company specializing in holographic gaming bringing immersive experience.|
 | BPN                   | BioPoly Networks              | A trailblazing firm engineering human tissues with 3D-bioprinting advanced methods.   |
 A> Utilize this AsciiDoc code to display the information about five innovative tech companies along with their abbreviations and brief descriptions:

 .Table of innovative tech companies
 [%header, options="header:best-fit"]
 |===
 | 3-Letter Acronym (TLA)| Name                        | Brief Description                                                                   
 |-----------------------|------------------------------|------------------------------------------------------------------------------------------
 | AIK                   | AI Knights                   | A ground-breaking company building the most advanced artificial intelligence systems. 
 | KGA                   | Kernel Genome Analytics     | A distinguished leader in genome sequencing and bioinformatics                     
 | GDS                   | Green Development Solutions   | A firm focusing on revolutionizing eco-friendly technologies for a sustainable future.
 | HPG                   | HoloPort Games               | A pioneering company specializing in holographic gaming to bring immersive experiences.
 | BPN                   | BioPoly Networks              | A trailblazing firm engineering human tissues with 3D-bioprinting advanced methods.    
 |===

 The AsciiDoc table organizes data on five tech companies with their TLAs, names, and brief descriptions.


 32% 32/100 [05:20<09:58,  8.80s/it]INFO 2024-06-26 21:20:19,675 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:20:24,555 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Transform this plain text list of ASIC miner manufacturers and their popular products into an AsciiDoc table:

 - Bitmain: AntMiner S9, AntMiner T9, AntMiner S17 Pro
 - MicroBT: WhatsMiner M20, WhatsMiner M30, WhatsMiner M31S
 - Canaan: AvalonMiner A9, AvalonMiner 1146, AvalonMiner 1166
 I> 
 A> Use this AsciiDoc syntax to convert the given list into a table format:

 .Popular ASIC miners manufacturer and model
 [%header]
 |===
 | Manufacturer         | Popular Products                                          
 |----------------------|-------------------------------------------------------------
 | Bitmain             | AntMiner S9, AntMiner T9, AntMiner S17 Pro                
 | MicroBT             | WhatsMiner M20, WhatsMiner M30, WhatsMiner M31S            
 | Canaan               | AvalonMiner A9, AvalonMiner 1146, AvalonMiner 1166          
 |===

 The AsciiDoc table exhibits popular ASIC miner manufacturers and their respective models.

 Q> Create an AsciiDoc table featuring at least three emissions-free vehicles with columns for the make, model, battery range, and efficiencies with details on the table below:

 - Make: Tesla
 - Model: Model 3 Long Range
 - Battery Range (miles): 353
 - Efficiency (MPGe): 138
 - Make: Volkswagen
 - Model: ID.4
 - Battery Range (miles): 260
 - Efficiency (MPGe): 104
 - Make: BMW
 - Model: iX3
 - Battery Range (miles): 256
 - Efficiency (MPGe): 105
 I> 
 A> You can apply this AsciiDoc code to structure emissions-free vehicles information into a table format:

 .Emissions-free vehicles
 [%header]
 |===
 | Make        | Model                  | Battery Range (miles) | Efficiency (MPGe)
 |-------------|------------------------|-----------------------|-----------------
 | Tesla       | Model 3 Long Range    | 353                   | 138
 | Volkswagen...
 ```arduino
  ID.4                   | 260                    | 104
  BMW                   | iX3                   | 256                    | 105
 |===

 The AsciiDoc table illustrates emissions-free vehicles' data presenting the make, model, battery range, and efficiency.


 34% 34/100 [05:39<09:52,  8.98s/it]INFO 2024-06-26 21:20:38,473 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Generate an AsciiDoc table containing information about three programming languages, their respective creators, and the years they were created.
 I> 
 A> Here's a sample AsciiDoc table containing information about several programming languages, their creators, and their creation years:

 .AsciiDoc table for programming languages
 [%header]
 |===
 | Language    | Creator                | Creation Year
 | Python      | Guido van Rossum      | 1989  
 | Java        | James Gosling          | 1995  
 | C#          | Anders Hejlsberg       | 2000  
 |===


 35% 35/100 [05:47<09:34,  8.83s/it]INFO 2024-06-26 21:20:46,618 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> How would you represent a table with horizontal alignments in AsciiDoc?
 I> 
 A> To create a table with horizontal alignments in AsciiDoc, you can use colon characters as part of the separator to indicate the desired alignment:

 .Table with horizontal alignment
 [%header, cols="^ center left ^"]
 |===
 | Column A | Column B      | Column C
 | Cell A1  | Cell B1       | Cell C1
 | Cell A2  | Cell B2       | Cell C2
 |===
 In this example, the 'left' alignment is used for the second column to demonstrate using the alignments.

 Q> Create an AsciiDoc table representing the top 3 highest-grossing movies of all time, their release years, and their worldwide gross revenues.
 I> 
 A> Here's a representation of an AsciiDoc table for the top 3 highest-grossing movies of all time, along with their release years and gross revenues:

 .Top 3 highest-grossing movies
 [%header]
 |===
 | Movie                                           | Release Year | Worldwide Gross Revenue   
 | Avengers: Endgame                               | 2019         | $2,797,800,564
 | Avatar                                           | 2009         | $2,789,709,882
 | Titanic                                          | 1997         | $2,186,772,302
 |===


 37% 37/100 [05:59<08:07,  7.74s/it]INFO 2024-06-26 21:20:57,804 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> In an AsciiDoc table, how do you merge two cells vertically and center aligned while keeping the rest justified left?
 I> 
 A> To merge two cells vertically and center align while keeping the rest justified left in an AsciiDoc table, you would use the '^' character for alignment followed by the merge attribute enclosed within plus signs ('+'):

 .Merged and centered cell example
 [%header, cols="^ left + center(+) + left ^"]
 |===
 | Column A    | Column B          | Column C
 | Cell A1     | Merged and centered | Cell C1
 | Cell A2     | Cell B2           | Cell C2
 |===
 The '(+)' syntax inside the 'center' attribute is to merge the cells horizontally while centering the content.

 Q> Generate an AsciiDoc table showcasing different programming languages, their creators, and their release years.
 I> 
 A> Here's an AsciiDoc table with the given information about programming languages, creators, and their release years:

 .Popular programming languages with creators and release years
 [%header]
 |===
 | Language      | Creator      | Release Year
 |---------------|--------------|--------------
 | C             | Dennis Ritchie  | 1972
 | C++           | Bjarne Stroustrup | 1985
 | Python        | Guido van Rossum | 1991
 | Java          | James Gosling  | 1995
 | JavaScript     | Brendan Eich        | 1995
 | Ruby          | Yukihiro 'Matz' Matsumoto | 1995
 |===

 This table can help you better understand the evolution of programming languages and their creators.


 39% 39/100 [06:10<07:16,  7.15s/it]INFO 2024-06-26 21:21:09,637 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Can you generate an AsciiDoc table displaying credit card payment details, including each card type's maximum limit, interest rate, and annual fee?
 I> 
 A> Here's the AsciiDoc code for a table containing credit card payment details:

 .Credit Card Payment Details
 [%header, options="header:best-fit"]
 |===
 | Card Type     | Maximum Limit (USD) | Interest Rate (%) | Annual Fee (USD) |
 | Visa          | 50,000              | 18.5               | 100              |
 | Mastercard    | 50,000              | 18.5               | 100              |
 | American Express   | 30,000 | 20.25  | 200     |
 | Discover       | 50,000              | 18.5               | 100              |
 | Diners Club    | 30,000              | 20.25               | 300              |
 | Union Pay      | 50,000              | 18.5               | 150              |
 |===

 Q> Create an AsciiDoc table with 2 columns: fixed-width and paragraph-style cells.
 I> 
 A> Here's the AsciiDoc code for a table displaying both fixed-width and paragraph-style cells:

 .Table with fixed-width and paragraph-style cells
 [%header, options=",align=center,cols=*,width=20"]
 |===
 | Column 1         | Column 2 (p)          |
 | Over 600px       | Content               |
 | 20px * 3         | **Bold (p)**           |
 |`code`           | Monospace (p)         |
 |                 | Right-aligned (p):       |
 |                 |                       |
 |                 |     _Italic (p)_       |
 |                 |                       |
 |                 | (Parentheses (p))       |
 |===


 41% 41/100 [06:23<06:46,  6.88s/it]INFO 2024-06-26 21:21:22,248 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Create an AsciiDoc table with at least three technologies sorted by their year of introduction, including the name, category, and milestone.
 I> * Technologies: 
 1. 5G, 2019, Communications
 2. Li-Fi, 2011, Data Communications
 3. Blockchain, 2008, Financial Services
 A> Use this AsciiDoc code to represent the table for given technologies-

 .Major Technologies and their Introduction
 [%header]
 |===
 | Name         | Category             | Year of Introduction
 | 5G           | Communications      | 2019
 | Li-Fi        | Data Communications   | 2011
 | Blockchain   | Financial Services   | 2008
 |===

 Table summarizing the key technologies alongside their category and the year of introduction.

 Q> Extract information from a table to display the average monthly rainfall in centimeters for cities of Los Angeles, New York, and Chicago for the past 12-month period.
 I> .Rainfall data for the last 12 months in major US Cities
 | City        | January (cm) | February (cm) | March (cm)  | April (cm) | May (cm)  | June (cm) | July (cm)  | August (cm) | September (cm) | October (cm)| November (cm) | December (cm)
 | Los Angeles  | 6.8          | 6.7          | 10.2        | 8.3          | 12.1      | 13.8      | 4.7         | 5.6          | 9.8           | 5.7         | 3.8           | 5.9         
 | New York    | 7.6          | 6.3          | 6.7         | 9.3          | 11.1      | 10.7      | 9.0         | 9.2          | 5.1           | 6.9         | 6.0           | 4.5         
 | Chicago     | 9.4          | 7.9          | 9.7         | 10.2         | 10.1      | 9.2       | 11.4        |10.8          | 3.2           | 9.9         | 6.9           | 8.7
 A> To summarize the average rainfall data, apply this AsciiDoc code:

 .Average Monthly Rainfall for Last 12 Months
 [%header]
 | City        | Avg. Monthly Rainfall (cm)
 | Los Angeles  | 8.45
 | New York    | 7.83
 | Chicago     | 9.05


 43% 43/100 [06:37<06:33,  6.91s/it]INFO 2024-06-26 21:21:36,200 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> How would an AsciiDoc table look like for 2021 GDP data with countries, GDP, and GDP ranking in billions of dollars?
 I> 
 A> Here's an example of an AsciiDoc table for 2021 GDP data:

 .2021 GDP data
 [%header, options="header:center"]
 |===
 | Rank   | Country            | GDP (Bn USD) |
 |--------|--------------------|--------------|
 | 1      | United States      | 22,670       |
 | 2      | China              | 16,140       |
 | 3      | Japan              | 5,090        |
 | 4      | Germany            | 4,230        |
 | 5      | United Kingdom      | 2,620        |
 | 6      | India              | 2,660        |
 | 7      | France             | 2,650        |
 | 8      | Italy              | 2,250        |
 | 9      | Canada             | 1,680        |
 | 10     | South Korea         | 1,640        |
 |===

 The table below displays the Gross Domestic Product (GDP) in billions of US dollars for the top 10 economies in 2021, ordered by rank.

 Q> Convert the given CSV data of sales data for 2021 and 2022 into AsciiDoc table format.
 I> Year,Salesperson,Sales (USD)
 2021,Alex,85000
 2021,Jamie,92000
 2021,Taylor,95000
 2021,Lena,87000
 2022,Alex,90000
 2022,Jamie,101000
 2022,Taylor,112000
 2022,Lena,108000
 A> Transform the given CSV data to an AsciiDoc table:

 .Comparison of 2021-2022 sales data for Alex, Jamie, Taylor, and Lena
 [%header, options="header:right"]
 |===
 | Year    | Salesperson  | Sales (USD)
 |---------|--------------|-------------
 | 2021    | Alex         | 85000
 | 2021    | Jamie        | 92000
 | 2021    | Taylor       | 95000
 | 2021    | Lena         | 87000
 | 2022    | Alex         | 90000
 | 2022    | Jamie        | 101000
 | 2022    | Taylor       | 112000
 | 2022    | Lena         | 108000
 |===

 The metric used in this table is the sales numbers in US dollars for Alex, Jamie, Taylor, and Lena, tracked by year, for 2021 and 2022.


 45% 45/100 [06:52<06:33,  7.15s/it]INFO 2024-06-26 21:21:51,580 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Please generate an AsciiDoc table representing five countries with their land area, population, and gross domestic product (GDP) based on 2020 data.
 I> 
 A> Here's an AsciiDoc table with five countries, their land area, population, and 2020 GDP:

 .Table of five countries with their land area, population, and GDP in 2020
 [%header, options="header:best-fit"]
 |===
 | Country       | Land Area (km²) | Population  (as of 2020)  | GDP  (USD Billions, as of 2020) |
 |---------------|------------------|-----------------------|--------------------------------|
 | China          | 9,596,961        | 1,411,000,000         | 14,340                        |
 | United States| 9,833,517        | 331,002,651            | 20,934                        |
 | Russia       | 17,098,242       | 146,767,000            | 1,689                         |
 | Indonesia     | 1,919,440        | 273,523,615            | 1,125                         |
 | Brazil        | 8,515,767        | 212,559,417            | 1,445                         |
 |===

 This AsciiDoc table provides a comparison of five countries' land area, population, and GDP based on 2020 data.

 Q> Create an AsciiDoc table displaying three machine learning algorithms, their disadvantages, and real-life constraints where these algorithms can be inappropriate.
 I> 
 A> Here's an AsciiDoc table with three machine learning algorithms and their disadvantages along with real-life constraints where these algorithms can be inappropriate:

 .Table of machine learning algorithms, their disadvantages, and constraints
 [%header, options="header:best-fit"]
 |===
 | Algorithm          | Disadvantage                       | Real-life constraint                                              |
 |--------------------|------------------------------------|------------------------------------------------------------------|
 | Linear Regression  | Assumes linear relationships           | Dataset with too many variables, duplicate variables, or complex relationships |
 | Decision Trees       | Overfitting the data         | Datasets with missing data, categorical variables with many unique values, or continuous variables |
 | Neural Networks     | Needs a large amount of data        | Datasets with high-dimensional feature space, limited training data, or short time for training |
 |===

 This AsciiDoc table presents three machine learning algorithms, their respective disadvantages, and real-life constraints.


 47% 47/100 [07:07<06:18,  7.15s/it]INFO 2024-06-26 21:22:05,849 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Create an AsciiDoc table presenting the budget of five cities with columns for the city, population, total budget, and allocated budget per capita.
 I> City name: **New York**, Population: **8,419,282**, Total budget: **$89,179,000,000**, Budget per capita: **$10,600.85**
 A> Here's an AsciiDoc table presenting the budget of five cities including New York, with columns for the city, population, total budget, and allocated budget per capita:

 .Five-city budget comparison
 [%header, options="header:best-fit"]
 |===
 | City                    | Population       | Total Budget  | Budget Per Capita   
 |-------------------------|-----------------|--------------|---------------------|
 | New York                | 8,419,282        | $89,179,000,000   | $10,600.85    
 | Tokyo                  | 9,694,000       | $62,111,000,000   | $6,396.74    
 | Los Angeles            | 4,000,000        | $10,579,000,000   | $2,644.75    
 | São Paulo               | 12,277,000       | $25,621,000,000   | $2,085.25    
 | London                 | 8,961,000        | $62,683,000,000   | $6,996.26    
 |===

 Please note that the numbers listed in this example table are based on fictitious and rounded budget data.

 Q> Generate an AsciiDoc table listing the eight planets in our solar system with their corresponding orbital periods and average distances from the Sun in astronomical units (AU).
 I> 
 A> Here's an AsciiDoc table listing the eight planets in our solar system with their corresponding orbital periods and average distances from the Sun in astronomical units (AU):

 .Comparison of solar system planets
 [%header, options="header:best-fit"]
 |===
 | Planet         | Orbital Period (Earth Year) | Avg. Distance from Sun (AU)
 |----------------|--------------------------|-----------------------------|
 | Mercury        | 0.24               | 0.39                         
 | Venus          | 0.62               | 0.72                         
 | Earth          | 1                        | 1                           
 | Mars           | 1.88                | 1.52                         
 | Jupiter       | 11.86              | 5.20                         
 | Saturn         | 29.46              | 9.58                         
 | Uranus         | 84.01              | 19.18                        
 | Neptune        | 165.00             | 30.07                        
 |===

 Please note that the orbital periods and average distances listed in this example table are based on factual data.


 49% 49/100 [07:22<06:12,  7.30s/it]INFO 2024-06-26 21:22:21,142 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Extract and format information about famous paintings, artists, and their creation years into an Asciidoc table.
 I> 
 A> Following is the AsciiDoc code for the requested table containing famous paintings, artists, and their creation years:

 .Famous Paintings and Artists
 [%header, options="header:best-fit"]
 |===
 | Painting                     | Artist   | Creation Year |
 | Mona Lisa                    | Leonardo da Vinci   | 1503-1506     |
 | Starry Night                 | Vincent van Gogh | 1889         |
 | The Persistence of Memory    | Salvador Dalí    | 1931         |
 | The Last Supper              | Leonardo da Vinci   | 1498         |
 | The Scream                   | Edvard Munch    | 1893         |
 | Guernica                     | Pablo Picasso   | 1937         |
 | The Night Watch              | Rembrandt      | 1642         |
 | The Arnolfini Portrait       | Jan van Eyck    | 1434         |
 | Girl with a Pearl Earring    | Johannes Vermeer  | 1665         |
 | The Birth of Venus             | Sandro Botticelli | 1485         |
 |===

 Q> Convert the list of top programming languages and respective popularity percentages into an Asciidoc table format.
 I> 
 A> The AsciiDoc table in the requested format with the list of top programming languages and popularity percentages is provided below:

 .Top Programming Languages and Popularity
 [%header, options="header:best-fit"]
 |===
 | Language         | Popularity (%) |
 | JavaScript      | 11.7           |
 | Python          | 10.1           |
 | Java            | 8.2            |
 | C#              | 7.3            |
 | C++             | 6.2            |
 | TypeScript      | 3.9            |
 | PHP             | 3.8            |
 | Ruby            | 3.0            |
 | Swift           | 2.9            |
 | Kotlin          | 2.3            |
 |===


 51% 51/100 [07:35<05:44,  7.04s/it]INFO 2024-06-26 21:22:34,029 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Generate an Asciidoc table to display the nutrition facts of 100g of dark chocolate, such as calories, fats, and carbohydrates.
 I> 
 A> Here's an example AsciiDoc table for nutrition facts of 100g dark chocolate:

 .Nutrition facts of 100g dark chocolate
 [%header]
 | Nutrient       | Amount    |
 | Calories      | 546 kcal   |
 | Total Fat     | 44.2g     |
 | Saturated Fat | 25.3g     |
 | Carbohydrates | 45.9g     |
 | Fiber         | 11.2g     |
 | Sugars        | 23.2g     |

 This table presents the nutrition facts of 100g dark chocolate.

 Q> Formulate an Asciidoc table using data from the five best-performing Marvel movies in terms of global box office gross.
 I> 
 A> Here's an example AsciiDoc table for the five best-performing Marvel movies in terms of global box office gross:

 .Five best-performing Marvel movies by global box office gross
 [%header]
 | Rank  | Marvel Movie              | Global Box Office Gross (USD)    |
 | 1     | The Avengers              | 1,518,815,482                  |
 | 2     | Avengers: Infinity War    | 2,048,359,754                  |
 | 3     | Avengers: Endgame         | 2,797,800,564                  |
 | 4     | Black Panther            | 1,346,913,161                  |
 | 5     | Captain Marvel            | 1,128,274,794                  |

 This table illustrates the five best-performing Marvel movies in terms of global box office gross.


 53% 53/100 [07:47<05:19,  6.80s/it]INFO 2024-06-26 21:22:46,537 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Generate an Asciidoc table that organizes the top 10 most populous countries globally along with their populations and areas in square kilometers.
 I> 
 A> Use the given data to construct the Asciidoc table:

 .Top 10 most populous countries and their areas
 [%header, options="header:best-fit"]
 |===
 | Country              | Population       | Area (sq. km)  |
 |---------------------|-----------------|--------------|
 | China                | 1,411,000,000   | 9,600,000    |
 | India               | 1,353,000,000   | 3,287,263    |
 | United States       | 332,000,000     | 9,833,517    |
 | Indonesia           | 273,500,000     | 1,919,440    |
 | Pakistan           | 231,000,000     | 881,913     |
 | Brazil              | 213,000,000     | 8,511,965   |
 | Nigeria             | 210,000,000     | 923,768     |
 | Bangladesh          | 164,000,000     | 147,570     |
 | Russia              | 143,700,000     | 17,098,242  |
 | Mexico              | 130,800,000     | 1,964,375   |
 |===

 The provided table presents the data on the top 10 most populous countries, along with their respective population and area (in square kilometers).

 Q> Tabulate the performance metrics of well-known AI models, lists their creators, and showcases their most common real-world applications in an AsciiDoc table.
 I> 
 A> Create an AsciiDoc table comprising information about various famous AI models, their creators, and real-world applications using the following information:

 .Prominent AI models, their creators, and real-world applications
 [%header, options="header:best-fit"]
 |===
 | AI Model            | Creator          | Typical Applications                   |
 |--------------------|------------------|---------------------------------------|
 | AlphaGo          | Google           | Game-playing (Go, chess)               |
 | Siri              | Apple            | Voice assistance (iPhones, HomePods)   |
 | Alexa             | Amazon           | Voice assistance, smart home control   |
 | Tesla Autopilot   | Tesla            | Self-driving (cars)                    |
 | Google Translate   | Google           | Language translation (text, speech)    |
 | IBM Watson         | IBM              | Cognitive computing, Q&A, text analytics |
 | Microsoft Cortana   | Microsoft        | Voice assistance (PCs, mobile phones)  |
 | OpenAI GPT-3       | OpenAI           | Text generation, question-answering    |
 | Face++             | Megvii          | Face recognition, image analysis        |
 | trickyRicky       | Ricky            | AI Consulting                          |
 |===

 The AsciiDoc table lists renowned AI models, their creators, and common real-world applications.


 55% 55/100 [08:03<05:19,  7.11s/it]INFO 2024-06-26 21:23:02,198 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Construct an AsciiDoc table with columns for ten programming languages, a brief description of their use cases, and an example of popular library or framework.
 I> 
 A> Here's an AsciiDoc table presenting ten programming languages, along with their use cases and popular libraries or frameworks:

 .Ten programming languages with use cases and popular libraries/frameworks
 [%header, options="header:best-fit"]
 |===
 | Language        | Use Case                               | Popular Library/Framework
 |-----------------|-----------------------------------------|-----------------------------
 | Python          | General-purpose, scientific computing   | NumPy, pandas, Django     
 | JavaScript      | Web development                         | React, Angular, Node.js    
 | Java            | Enterprise applications, Android          | Spring, Hibernate, Android SDK
 | C#              | Windows application development          | .NET Framework, Unity     
 | R              | Statistical computing, data analysis     | ggplot2, caret            
 | Swift           | iOS development                         | SwiftUI, UIKit            
 | Ruby            | Web development, automation               | Ruby on Rails, RSpec      
 | C++             | System/application software, game       | Qt, STL                   
 | PHP             | Web development                         | Laravel, Symfony          
 | Golang         | Backend development, cloud computing    | Gin, Kubernetes           
 |===

 Please note that the libraries and frameworks listed may not cover the full potential of the respective programming languages and are not ranked in any particular order.

 Q> Design an AsciiDoc table with columns for five countries, their respective official languages, area (in km²), and population (as of 2021).
 I> Country: **China**, Official language: **Mandarin Chinese**, Area: **9,600,000 km²**, Population: **1,411,165,269**
 A> Here's an AsciiDoc table comparing five countries, their official languages, areas, and population (as of 2021), including the provided information about China:

 .Comparison of five countries
 [%header, options="header:best-fit"]
 |===
 | Country                  | Official Language          | Area (km²)    | Population (as of 2021)
 |-------------------------|---------------------------|---------------|------------------------
 | China                    | Mandarin Chinese           | 9,600,000     | 1,411,165,269         
 | Russia                  | Russian                   | 17,098,242   | 145,934,462            
 | Canada                  | English, French            | 9,984,670     | 38,048,737             
 | United States           | English                   | 9,833,517     | 333,215,054            
 | Indonesia               | Indonesian                | 1,910,931     | 275,226,352            
 |===

 Please note that the numbers listed in this example table are based on potentially rounded area and population data and may not reflect the most current data.


 57% 57/100 [08:18<05:11,  7.24s/it]INFO 2024-06-26 21:23:17,265 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:23:23,071 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Generate an AsciiDoc table containing data about prominent Nobel Prize categories, the most recent prizes awarded, and notable laureates for each category.
 I> 
 A> Below is an AsciiDoc table showcasing some Nobel Prize categories, the latest years the prizes were awarded, and notable laureates in those categories:

 .Nobel Prize categories, latest years awarded, and notable laureates
 [%header, options="header:best-fit"]
 |===
 | Category        | Latest Year Awarded | Notable Laureates
 |-----------------|--------------------|-----------------
 | Physics         | 2019              | Marie Curie, Albert Einstein
 | Chemistry       | 2019              | Dorothy Hodgkin, Linus Pauling
 | Medicine        | 2019              | Elizabeth Blackburn, Françoise Barré-Sinoussi
 | Literature      | 2020              | Toni Morrison, Kazuo Ishiguro
 | Peace           | 2021              | Malala Yousafzai, Maria Ressa
 | Economic Sciences| 2019             | Abhijit Banerjee, Esther Duflo
 |===

 Please note that the notable laureates mentioned are not an exhaustive list and are simply representatives for each category.

 Q> Build an AsciiDoc table for ten countries, their capitals, and the official languages spoken in each, along with the populations.
 I> 
 A> Here's an AsciiDoc table with data for ten countries, their capitals, official languages, and populations:

 .Ten countries, their capitals, official languages, and populations
 [%header, options="header:best-fit"]
 |===
 | Country        | Capital          | Official Language(s)           | Population (as of 2021)
 |----------------|-----------------|------------------------------|---------------------
 | China          | Beijing         | Mandarin                     | 1,411,000,000
 | India          | New Delhi       | Hindi, English                | 1,380,000,000
 | United States  | Washington, D.C.| English                      | 331,000,000
 | Indonesia      | Jakarta         | Indonesian                   | 273,000,000
 | Pakistan       | Islamabad       | Urdu, English                 | 225,000,000
 | Brazil         | Brasilia        | Portuguese                    | 212,000,000
 | Nigeria        | Abuja           | English, Hausa, Yoruba        | 206,000,000
 | Bangladesh    | Dhaka           | Bengali                      | 164,000,000
 | Russia         | Moscow          | Russian                      | 146,000,000
 | Mexico        | Mexico City      | Spanish                      | 128,000,000
 |===

 Kindly note that the population figures might not be perfectly up-to-date and are approximated based on available data and the latest available estimates.


 59% 59/100 [08:39<05:34,  8.17s/it]INFO 2024-06-26 21:23:37,907 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Generate an AsciiDoc table for displaying the mean and standard deviation of two data sets, A and B.
 I> DataSet A: [3.2, 5.2, 3.8, 4.9, 5.1]
 DataSet B: [6.4, 7.0, 8.2, 7.4, 7.8]
 A> Here's an AsciiDoc table presenting the mean and standard deviation of data sets A and B:

 .Mean and Standard Deviation of Data Sets A and B
 [%header, options="header:best-fit"]
 |===
 | Data Set      | Mean         | Standard Deviation
 |---------------|-------------|-------------------
 | Data Set A    | 4.66        | 0.82             
 | Data Set B    | 7.24        | 0.47             
 |===

 The mean and standard deviation values presented in the example table are calculated based on fictitious datasets A and B.

 Q> Explain how to format cell borders in AsciiDoc tables.
 I> 
 A> In AsciiDoc, to format cell borders, you can use various characters such as |, -, =, and ^ as part of the separator. For instance, '=' can be used to emphasize the header, and leading '^' characters can be used for merging cells.

 .Formatting AsciiDoc Cell Borders
 [%header, cols="^ , , ^"]
 |===
 | ^   | Column A| Column B   | ^   |
 |------|-------- |-----------|-----|
 | Row  | Cell A1 | Cell B1   | Row  |
 | 1   | Cell A2 | Cell B2   | 2   |
 |------|-------- |-----------|-----|
 | Row  | Cell A3 | Cell B3   | Row  |
 | 3   | Cell A4 | Cell B4   | 4   |
 |===

 This example demonstrates using the '=' characters to emphasize the headers, and merging the first and last rows of the table.


 61% 61/100 [08:51<04:55,  7.57s/it]INFO 2024-06-26 21:23:50,303 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Extract the 3rd column from the following AsciiDoc table, which demonstrates the distribution of cryptocurrencies by market capitalization.
 I> .Cryptocurrency market capitalization distribution
 | Rank     | Cryptocurrency   | Market Cap   |
 |----------|-----------------|--------------|
 | 1        | Bitcoin         | $1,043,477,607,099.24  |
 | 2        | Ethereum       | $216,963,501,358.73 |
 | 3        | Binance Coin   | $69,435,086,311.82  |
 | 4        | Cardano        | $68,665,918,676.23 |
 | 5        | Ripple         | $57,007,981,633.89 |
 A> For extracting the 3rd column, you can use the data from the 'Market Cap' column, which contains the market capitalization of each cryptocurrency. The extracted values are:

 * $1,043,477,607,099.24
 * $216,963,501,358.73
 * $69,435,086,311.82
 * $68,665,918,676.23
 * $57,007,981,633.89

 Q> Identify the type of the data displayed in the following AsciiDoc table, which depicts the most common causes of death in the US for 2019.
 I> .Leading causes of death in the U.S., 2019
 | Rank     | Cause of Death | Number    |
 |----------|---------------|-----------|
 | 1        | Heart disease | 659,041   |
 | 2        | Cancer       | 599,108   |
 | 3        | COVID-19     | 345,323   |
 | 4        | Accidents    | 169,936   |
 | 5        | Stroke       | 150,005   |
 A> The AsciiDoc table clasifies the data as categorical (cause of death), continuous (number), and ordinal (rank). The data is related to the leading causes of death in the U.S. for 2019.


 63% 63/100 [09:05<04:32,  7.36s/it]INFO 2024-06-26 21:24:03,999 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Explain the process to categorize your Git repositories using an AsciiDoc table and provide examples for three repositories.
 I> | Repository Name           | Category                 | Description                                                                 |
 |--------------------------|--------------------------|-----------------------------------------------------------------------------|
 | awesome-python-libs     | Python Libraries         | A curated list of awesome Python libraries for a variety of purposes.        |
 | eco-friendly-apps        | Mobile Apps             | A collection of mobile apps catering to eco-friendly and sustainable lifestyle.|
 | motion-tracking-algorithms| Algorithms              | Implementations of popular algorithms and techniques for motion tracking.      |
 A> To categorize Git repositories using an AsciiDoc table, perform the following steps:

 1. Define the table structure with headers for the repository name, category, and description.
 2. Insert entries for your repositories in the same format as the provided example.

 For example:

 .Table for categorizing repositories
 [%header, options="header:best-fit"]
 |===
 | Repository Name           | Category                 | Description                                                                 |
 |--------------------------|--------------------------|-----------------------------------------------------------------------------|
 | awesome-python-libs     | Python Libraries         | A curated list of awesome Python libraries for a variety of purposes.        |
 | eco-friendly-apps        | Mobile Apps             | A collection of mobile apps catering to eco-friendly and sustainable lifestyle.|
 | motion-tracking-algorithms| Algorithms              | Implementations of popular algorithms and techniques for motion tracking.      |
 |===

 Follow this AsciiDoc table structure to display the categorized information for your Git repositories.

 Q> In an AsciiDoc table, illustrate the top colleges according to a specific metric, such as job placement rate.
 I> 
 A> Construct an AsciiDoc table to display the top colleges regarding a selected metric, e.g. job placement rate.

 .Top colleges based on job placement rates
 [%header, options="header:best-fit"]
 |===
 | University       | Job Placement Rate   | Notable Alumni                                                                 |
 |-----------------|---------------------|-----------------------------------------------------------------------------------|
 | Massachusetts Institute of Technology (MIT) | 90%  | Kofi Annan, Buzz Aldrin                                                      |
 | Stanford University              | 87%  | Reid Hoffman, Elon Musk                                                        |
 | California Institute of Technology (Caltech) | 85%  | Frank Capra, Frank Gehry                                                         |
 | University of Oxford          | 83%  | Stephen Hawking, Indira Gandhi                                                    |
 | Carnegie Mellon University   | 82%  | Andy Bechtolsheim, Vinod Khosla                                                  |
 |===

 The AsciiDoc table below outlines the top colleges according to their distinguished job placement rates.


 65% 65/100 [09:19<04:15,  7.30s/it]INFO 2024-06-26 21:24:18,337 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:24:22,386 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Create an AsciiDoc table that itemizes five frequently consumed fruits along with their sugar content, vitamin C concentration, and their origin country.
 I> 
 A> This AsciiDoc table displays five frequently consumed fruits with relevant data on sugar content, vitamin C, and country of origin:

 .Table showing sugar content, vitamin C concentration, and fruit's origin country
 [%header, options="header:best-fit"]
 |===
 | Fruit                | Sugar Content (grams) | Vitamin C (mg)  | Origin Country             |
 |----------------------|----------------------|----------------|----------------------------|
 | Apple                | 19                   | 4.6            | Kazakhstan                 |
 | Banana               | 14                   | 8.7            | Southeast Asia              |
 | Orange               | 9.3                  | 53.2           | China ('Citrus sinensis')   |
 | Pineapple            | 13.8                 | 79.1           | South America               |
 | Strawberry           | 7                    | 58.8           | France                     |
 |===

 This AsciiDoc table displays information on five common fruits alongside sugar content and vitamin C concentration as well as their origin countries.

 Q> Generate an AsciiDoc table containing five programming languages, with details on the language designer, introduction year, and pedigree (dynamic or static).
 I> 
 A> This AsciiDoc table includes details on five programming languages, listing their designers, introduction years, and respective classifications (dynamic or static):

 .Table of five programming languages with designer, introduction year, and pedigree
 [%header, options="header:best-fit"]
 |===
 | Language      | Designer   | Introduction Year | Pedigree               |
 |---------------|------------|------------------|-----------------------|
 | Python       | Guido van Rossum      | 1991             | Dynamic              |
 | C            | Dennis Ritchie      | 1972             | Static               |
 | Java         | James Gosling     | 1996             | Static               |
 | SQL          | Donald D. Chamberlin | 1974            | Dynamic              |
 | JavaScript    | Brendan Eich      | 1995             | Dynamic              |
 |===

 The AsciiDoc table provides details on five programming languages, including their designers, years of introduction, and either static or dynamic classification.


 67% 67/100 [09:36<04:13,  7.69s/it]INFO 2024-06-26 21:24:35,557 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:24:41,365 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:24:49,144 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Extract the bolded terms from this sentence: The **AsciiDoc** syntax is **intuitive** and **useful** for generating richly formatted documents, slides, and articles.
 I> The AsciiDoc syntax is intuitive and useful for generating richly formatted documents, slides, and articles.
 A> "AsciiDoc", "intuitive", and "useful"

 Q> List three advanced quantitative features of the Asciidoc language for table manipulation.
 I> 
 A> Some advanced quantitative features of Asciidoc for table manipulation include: 
 1. Calculations: Perform mathematical operations on columns, such as sum, average, and minimum.
 2. Grouping and filtering: Structure content in tabular format based on specific criteria.
 3. Conditional expressions: Display or hide content based on predefined conditions within the table data.


 69% 69/100 [10:00<04:36,  8.91s/it]INFO 2024-06-26 21:24:59,029 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Can you create an AsciiDoc table comparing the features and specifications of three top IoT smart home hubs?
 I> 
 A> Certainly, here is an AsciiDoc table comparing the features and specifications of three popular IoT smart home hubs from Amazon, Google, and Samsung:

 .Comparison of top IoT smart home hubs
 [%header, cols="^,^,^"]
 |===
 | Smart Home Hub | Features        | Specifications
 |----------------|----------------|----------------
 | Amazon Echo Plus| Voice assistant, smart home control, music playback, and more | Connects to Bluetooth, Zigbee devices, 3.0 USB, and Wi-Fi |
 | Google Nest Hub Max | Voice assistant, smart home control, and digital photo frame | Connects to Bluetooth, Wi-Fi and Chromecast compatible devices |
 | Samsung SmartThings Hub (3rd Gen) | Zigbee, Z-Wave, IP-based wireless communication and Bluetooth | Connects to Wi-Fi, Bluetooth LE |
 |===

 This table focuses on their features and connectivity options, showcasing their unique properties.

 Q> Provide a template of an AsciiDoc table to represent the five largest global economies, their GDPs, and their population sizes for a given year.
 I> 
 A> Here is an AsciiDoc table template that presents the five largest global economies, their GDPs, and their population sizes:

 .Global Economies, GDPs, and Population Sizes
 [%header, cols="^,^,^"]
 |===
 | Economy             | GDP         | Population |
 |---------------------|-------------|------------|
 | Largest Economy     | <GDP value>| <Population value> 
 | Second Largest    | <GDP value>| <Population value> 
 | Third Largest      | <GDP value>| <Population value> 
 | Fourth Largest     | <GDP value>| <Population value> 
 | Fifth Largest      | <GDP value>| <Population value> 
 |===

 To use the table template, replace the placeholders for the respective economies, GDP, and population values with the latest data.


 71% 71/100 [10:13<03:56,  8.15s/it]INFO 2024-06-26 21:25:11,829 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:25:18,330 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:25:26,582 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Contrast the features of four operating systems in an AsciiDoc table, including name, user interface, and kernel type.
 I> Operating System: **Windows 10**, User Interface: **GUI**, Kernel Type: **Hybrid**
 A> Here's an AsciiDoc table illustrating the features of several operating systems, including the provided example for Windows 10:

 .Comparison of operating systems
 [%header, options="header:best-fit"]
 |===
 | Operating System      | User Interface        | Kernel Type
 |----------------------|----------------------|---------------
 | Windows 10           | GUI                  | Hybrid       
 | Ubuntu              | GUI                  | Monolithic   
 | macOS               | GUI                  | Hybrid       
 | FreeBSD              | CLI, GUI             | Monolithic   
 |===

 Q> Extract the top five countries with the highest GDP from a list in a tabular format and display their related information in an AsciiDoc table.
 I> {"Afghanistan": 21.4, "Albania": 16.44, "Algeria": 167.3, "Andorra": 3.827, "Angola": 123.5, "Antigua and Barbuda": 1.873}
 A> Here's an AsciiDoc table using the input, which takes the top five countries with the highest GDP:

 .Top five countries with highest GDP
 [%header, options="header:best-fit"]
 |===
 | Country             | GDP (in billion dollars)
 |---------------------|-----------------------
 | Algeria             | 167.3               
 | Angola              | 123.5               
 | Afghanistan         | 21.4               
 | Albania             | 16.44              
 | Antigua and Barbuda  | 1.873              
 |===
 GDP numbers are based on the input provided, which might not be the latest or most accurate figures.


 73% 73/100 [10:40<04:23,  9.76s/it]INFO 2024-06-26 21:25:38,827 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Change the header background color to light blue for the previous table in Task 1.
 I> Refer to the table from Task 1.
 A> In order to change the header background color to light blue in the AsciiDoc table, you would need to add the attribute 'bgcolor="lightblue"' to the header row.

 However, as it currently stands, AsciiDoc does not support cell and row formatting with the exception of headings, columns, and alignment. As a result, you won't be able to modify the header background color using pure AsciiDoc syntax.

 Q> Generate an AsciiDoc table with a column for the date, and entries of fixed width for 'title' and 'description.'
 I> 
 A> Here's an AsciiDoc table with a fixed column width for 'title' and 'description' set to 25 characters.

 .Fixed Width Column Example
 [%header, options="header:best-fit;rows:shade"]
 |===
 | Date       | Title                     | Description
 | 2021-05-08 | AsciiDoc                | A text format, like |
 | 2021-05-01 | GPT Model               | The Generative |
 | 2021-06-15 | Machine Learning         | A subfield of artificial |
 |===

 In this example, we set the column width for the 'Title' and 'Description' columns to 25 characters by using the underscore (_) character to represent a fixed-width field.


 75% 75/100 [10:51<03:33,  8.52s/it]INFO 2024-06-26 21:25:50,106 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Generate an AsciiDoc table that lists five countries with their corresponding land area, population density, and location on the globe.
 I> 
 A> Here's the AsciiDoc code for a table listing five countries with their land area, population density, and location on the globe:

 .Table of Countries
 [%header, options="header:best-fit"]
 |===
 | Country        | Land Area (km2) | Population Density (people/km2) | Continent     |
 | Canada         | 9,984,670       | 4                              | North America |
 | China          | 9,596,961       | 151                            | Asia          |
 | Brazil         | 8,511,965       | 26                             | South America|
 | Russia         | 17,098,242      | 9                              | Europe        |
 | Australia      | 7,682,300       | 3                              | Australasia  |
 |===

 Q> Illustrate how to create a AsciiDoc table with merged columns, and offer an example with three columns of data.
 I> 
 A> To create a merged column in an AsciiDoc table, utilize colspecs (column specifications) with a character that duplicates in the next column. Here's a demonstration using three columns of data:

 .Table with merged columns
 -----------
 [%options=flow, cols="^Merge;Text;^Merge"]
 |===
 | ^Merge | Text               | ^Merge |
 | Canada  | Ottawa, Toronto, Vancouver  | Europe  |
 | Russia  | Moscow, Saint Petersburg       | Asia    |
 | Brazil  | Brasilia, Rio de Janeiro, Sao Paulo  | South America |
 |===


 77% 77/100 [11:03<02:58,  7.76s/it]INFO 2024-06-26 21:26:02,045 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Calculate the total number of employees working in each department of a company with the following given table of data.
 I> .Company Employee Count by Department
 | Department       | Number of Employees |
 | IT                | 260                |
 | Sales            | 180                |
 | Marketing        | 140                |
 | Product Development | 170              |
 | Support           | 150                |
 A> Applying the Asciidoc-formatted calculation, obtain the total employee count per department with:

 .Total Employees per Department
 [%header]
 | Department       | Total Employees      |
 | IT                | 260                 |
 | Sales            | 180                 |
 | Marketing        | 140                 |
 | Product Development | 170               |
 | Support           | 150                 |
 |-------------------|---------------------|
 | **TOTAL**          | **850**              |

 As demonstrated above, the company has a total of 850 employees distributed across several departments.

 Q> Compose a table that illustrates the product sales for the first quarter, detailing only the months of January and March for the three primary products of the ABC Company.
 I> 
 A> Refer to the following Asciidoc code to craft the product sales table for the first quarter focusing on January and March:

 .Q1 ABC Company Product Sales
 [%header, options="header:best-fit"]
 | Month   | Product | Sales      |
 | January  | Product A | 15,210   |
 | January  | Product B | 27,580   |
 | January  | Product C | 21,650   |
 | March    | Product A | 20,340   |
 | March    | Product B | 30,450   |
 | March    | Product C | 24,760   |

 Below is a table demonstrating the product sales reported by ABC Company for January and March of the first quarter.


 79% 79/100 [11:15<02:33,  7.32s/it]INFO 2024-06-26 21:26:14,646 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:26:18,176 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Generate an asciidoc table with data from the given CSV-formatted string, presenting a list of government expenses in a specific budget category.
 I> CSV string: "Category,Amount\nEducation,2700000000\nHealthcare,3800000000\nTransportation,1800000000"
 A> Here's the asciidoc code for the given CSV-formatted input:

 .Government Expenses in Specific Categories
 [%header]
 |===
 | Category           | Amount       |
 | Education          | 2700000000   |
 | Healthcare         | 3800000000   |
 | Transportation    | 1800000000   |
 |===


 80% 80/100 [11:25<02:33,  7.67s/it]INFO 2024-06-26 21:26:23,925 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Create an Asciidoc table presenting the details of three popular operating systems, including their release dates, latest stable versions, and market share (as of Q1 2022).
 I> 
 A> Below is the Asciidoc table that contains information about three popular operating systems along with their release dates, latest stable versions, and Q1 2022 market share.

 .Popular Operating Systems Information
 [%header, options="header:best-fit"]
 |===
 | Operating System | Release Date    | Latest Stable Version | Market Share (Q1 2022)   |
 | Microsoft Windows| November 20, 1985| Windows 11           | 75.89%                 |
 | macOS           | March 24, 2001 | macOS Monterey     | 17.49%                 |
 | Linux           | August 25, 1991| Ubuntu 21.04        | 3.55%                  |
 |===

 This Asciidoc table exhibits crucial details about the three widely-used operating systems, their market dominance in Q1 2022, and the most recent stable versions, with the release dates provided for perspective.

 Q> Provide a table in Asciidoc format summarizing the monthly rainfall and average temperatures (high and low) in a specific location, like Honolulu, Oahu, HI, during June 2021.
 I> 
 A> Here's the Asciidoc table summarizing the monthly rainfall and average temperatures (high and low) for Honolulu, Oahu, HI, during June 2021.

 .June 2021 Rainfall and Temperatures in Honolulu, Oahu, HI
 [%header, options="header:best-fit"]
 |===
 | Metric                  | June 2021       |
 | Monthly Rainfall (mm)  | 129            |
 | Average High Temperature (°F) | 85.9           |
 | Average Low Temperature (°F)| 72.2           |
 |===

 This Asciidoc table summarizes the June 2021 meteorological data in Honolulu, Oahu, HI, showcasing the monthly rainfall and average temperatures in Fahrenheit.


 82% 82/100 [11:38<02:11,  7.30s/it]INFO 2024-06-26 21:26:37,060 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:26:42,041 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Please provide an AsciiDoc table for the 2021 FIFA Women's World Cup groups, indicating participating teams, FIFA rankings, and their coaches.
 I> 
 A> Here is an AsciiDoc table for the 2021 FIFA Women's World Cup groups, with participating teams, FIFA rankings, and their coaches:

 .2021 FIFA Women's World Cup Groups
 [%header, options="header:best-fit"]
 |===
 | Group       | Team                                       | FIFA Ranking   | Coach
 |-------------|--------------------------------------------|---------------|-----------------------------------
 | A           | Netherlands                                 | 3              | Mark Parsons                     
 | A           | United States                               | 1              | Vlatko Andonovski                  
 | A           | Vietnam                                    | 34             | Mai Đức Chung                     
 | A           | Portugal                                   | 25             | Francisco Neto                    
 | B           | Germany                                    | 2              | Martina Voss-Tecklenburg           
 | B           | Spain                                      | 6              | Jorge Vilda                       
 | B           | China                                      | 14             | Shui Qingxia                     
 | B           | South Africa                                | 54             | Desiree Ellis                     
 | C           | Australia                                  | 10             | Tony Gustavsson                  
 | C           | Brazil                                     | 7              | Pia Sundhage                     
 | C           | Italy                                      | 16             | Milena Bertolini                  
 | C           | Jamaica                                     | 51             | Hubert Busby Jr.                 
 | D           | England                                    | 8              | Sarina Wiegman                   
 | D           | France                                     | 5              | Corinne Diacre                   
 | D           | Canada                                     | 7              | Bev Priestman                    
 | D           | Japan                                      | 11             | Asako Takakura                    
 |===

 This table is based on the groups drawn on October 22, 2021.

 Q> Kindly provide an AsciiDoc table with the top 5 smartphones in each price category: budget ($0-$300), mid-range ($300-$600), and premium ($600+).
 I> 
 A> Here is an AsciiDoc table with the top 5 smartphones in each price category: budget ($0-$300), mid-range ($300-$600), and premium ($600+):

 .Top 5 Smartphones by Price Category
 [%header, options="header:best-fit"]
 |===
 | Price Category | Smartphone                                   | Manufacturer | Operating System | Price Range
 |----------------|----------------------------------------------|--------------|-----------------|--------------
 | Budget         | Moto G Power (2021)                          | Motorola     | Android         | $249.99 - $299.99
 | Budget         | Samsung Galaxy A32 5G                         | Samsung      | Android         | $279.99
 | Budget         | TCL 20 Pro 5G                                | TCL          | Android         | $299.99 - $349.99
 | Budget         | OnePlus Nord N100                             | OnePlus      | Android         | $179.99 - $199.99
 | Budget         | Google Pixel 4a                              | Google       | Android         | $349
 | Mid-range      | Google Pixel 5a                               | Google       | Android         | $449
 | Mid-range      | Apple iPhone 11                               | Apple        | iOS             | $599
 | Mid-range      | Samsung Galaxy S20 FE 5G                        | Samsung      | Android         | $499.99 - $699.99
 | Mid-range      | OnePlus 9                                     | OnePlus      | Android         | $729
 | Mid-range      | Asus ZenFone 8                                | Asus         | Android         | $629.99 - $699.99
 | Premium        | Apple iPhone 13 Pro                            | Apple
 ```python
  | iOS             | $999
  | Premium        | Apple iPhone 13 Pro Max                | Apple       | iOS             | $1,099
  | Premium        | Samsung Galaxy Z Fold3 5G              | Samsung     | Android         | $1,799.99
  | Premium        | Samsung Galaxy S21 Ultra 5G             | Samsung     | Android         | $1,199.99 - $1,299.99
  | Premium        | Google Pixel 6 Pro                      | Google      | Android         | $699
  |===

 Please note that the prices and availability of smartphones may vary based on the providers and regions.
 ```


 84% 84/100 [12:02<02:22,  8.88s/it]INFO 2024-06-26 21:27:01,435 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> How would you display cumulative metrics for your website's monthly traffic in an AsciiDoc table?
 I> 
 A> To represent cumulative metrics for your website's monthly traffic, the AsciiDoc table might look like the example below.

 .Table with cumulative website traffic metrics
 [%header]
 |===
 | Month         | Unique Visitors   | Pageviews                 |
 | ---           | ---               | ---                       |
 | January 2023  | 12,500            | 37,500                    |
 | February 2023 | 8,000             | 45,000 (27.6% increase)    |
 | March 2023    | 14,000            | 70,000 (55.6% increase)    |
 | April 2023    | 10,500            | 85,500 (22.1% increase)    |
 | May 2023      | 19,000            | 114,000 (33.3% increase)   |
 | June 2023     | 15,000            | 144,000 (26.3% increase)   |
 | Total         | 89,000            | 493,000                   |
 |===

 This table breaks down website traffic by month and includes row-wise metrics with a percentage representing month-over-month growth. The cumulative metrics are shown in the last row.

 Q> Can you create an AsciiDoc data table using these education-related metrics for a group of universities?
 I> The input should be:

 .Education-related metrics
 [%header]
 | University      | Enrolled Students | Programs           |
 | ---             | ---               | ---               |
 | Harvard         | 20,971            | 362               |
 | MIT             | 11,470            | 216               |
 | Stanford        | 17,243            | 283               |
 | Yale            | 13,530            | 261               |
 | Berkley         | 41,827            | 350               |
 A> Applying the metrics you provided to create an AsciiDoc data table, the resulting table should look like this:

 .Table with education-related metrics for a group of universities
 [%header]
 |===
 | University      | Enrolled Students | Programs           |
 | ---             | ---               | ---               |
 | Harvard         | 20,971            | 362               |
 | MIT             | 11,470            | 216               |
 | Stanford        | 17,243            | 283               |
 | Yale            | 13,530            | 261               |
 | Berkley         | 41,827            | 350               |
 |===

 This table lists several universities, enrolled students, and programs they offer in an easy-to-understand AsciiDoc table format.


 86% 86/100 [12:17<01:58,  8.44s/it]INFO 2024-06-26 21:27:16,449 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:27:20,463 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:27:29,937 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Infer the markup to create an AsciiDoc table with the top five countries by land area and their populations.
 I> 
 A> To create an AsciiDoc table with the top five countries by land area and their populations, use the following markup:

 .The top five largest countries and their populations
 [%header, options="header:best-fit"]
 |===
 | Country        | Area (km²)      | Population (Millions)     |
 | Russia         | 17,098,242     | 145.9                   |
 | Canada        | 9,984,670      | 37.7                    |
 | China         | 9,600,012      | 1,439.3                 |
 | United States  | 9,629,091      | 331.9                   |
 | Brazil        | 8,511,965      | 213.2                   |
 |===

 This table demonstrates how to create a table with the specified criteria.

 Q> What is the proper syntax for generating an AsciiDoc table with three columns, using bold headings?
 I> 
 A> To generate an AsciiDoc table with three columns, using bold headings, use the following syntax:

 [%header, options="header:best-fit"]
 |====
 | **Column 1** | **Column 2**               | **Column 3**          
 |-------------|---------------------------|------------------|
 | data1       | data2, further explained  | data3           
 | data4       | data5                     | data6           
 |...           |...                        | ...             
 |====

 The rows are formed using vertical bars `|`, and the cells are defined by enclosing each column entry with these vertical bars.


 88% 88/100 [12:43<01:57,  9.80s/it]INFO 2024-06-26 21:27:42,012 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Infer the respective contribution percentages for the "Major Causes of Deforestation" and represent them as a table in Asciidoc format.
 I> * Agriculture: 32%
 * Urbanization: 28%
 * Mining: 14%
 * Logging: 12%
 * Fires: 10%
 * Infrastructure: 4%
 A> Here's the AsciiDoc table representing the contribution percentages for the major causes of deforestation:

 .Contributions to deforestation
 [%header, options="header:best-fit"]
 |===
 | Cause                     | Contribution (%) |
 | Agriculture              | 32%              |
 | Urbanization             | 28%              |
 | Mining                   | 14%              |
 | Logging                   | 12%              |
 | Fires                    | 10%              |
 | Infrastructure            | 4%               |
 |===

 The table presents the given input converted to AsciiDoc format with appropriate percentages for the major causes of deforestation.

 Q> Determine the daily sales of three products by your company for the last working week (Monday to Friday) and turn the information into an Asciidoc table.
 I> * Monday: Product A - 100, Product B - 85, Product C - 130
 * Tuesday: Product A - 120, Product B - 90, Product C - 115
 * Wednesday: Product A - 110, Product B - 100, Product C - 125
 * Thursday: Product A - 95, Product B - 80, Product C - 133
 * Friday: Product A - 105, Product B - 95, Product C - 120
 A> Here's the AsciiDoc table representing the daily sales of three products over the last working week:

 .Daily sales for last working week
 [%header, options="header:best-fit"]
 |===
 | Day          | Product A | Product B | Product C |
 | Monday       | 100       | 85        | 130      |
 | Tuesday      | 120       | 90        | 115      |
 | Wednesday    | 110       | 100       | 125      |
 | Thursday     | 95        | 80        | 133      |
 | Friday       | 105       | 95        | 120      |
 |===

 The table is populated with the daily sales data provided for each product over the last working week.


 90% 90/100 [12:56<01:28,  8.89s/it]INFO 2024-06-26 21:27:55,701 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> How would you display a table with AsciiDoc that shows the quantity of different fruits, and their price per kilogram?
 I> | Fruit       | Quantity (kg) | Price (AUD) per kg |
 |-------------|---------------|-------------------|
 | Apples      |       10        |      2.00         |
 | Bananas     |       20        |      1.50         |
 | Oranges     |       15        |      3.00         |
 | Mangoes     |       30        |      1.75         |
 | Grapes      |        5        |      8.00         |
 A> Use this AsciiDoc code for the table:

 .Fruit Prices Table in AsciiDoc
 [%header, options="header:best-fit;rows:shade"]
 |===
 | Fruit    | Quantity (kg) | Price (AUD) per kg |
 | Apples    | 10            | 2.00              |
 | Bananas   | 20            | 1.50              |
 | Oranges   | 15            | 3.00              |
 | Mangoes   | 30            | 1.75              |
 | Grapes    |  5            | 8.00              |
 |===

 Q> In AsciiDoc format, present a table that shows your company's sales by region and by month.
 I> 
 A> This AsciiDoc table displays the sales by region and month:

 .Monthly Sales by Region
 [%header, options="header:best-fit;rows:shade"]
 |===
 | Region    | Jan Sales | Feb Sales | Mar Sales | Apr Sales |
 |-----------|-----------|-----------|-----------|-----------|
 | North     | 3000      | 3200      | 3400      | 3700      |
 | South     | 2000      | 2100      | 2400      | 2500      |
 | East      | 4000      | 4300      | 4500      | 4800      |
 | West      | 2500      | 2700      | 2800      | 3000      |
 |-----------|-----------|-----------|-----------|-----------|


 92% 92/100 [13:10<01:05,  8.20s/it]INFO 2024-06-26 21:28:08,975 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Compare the given financial data for two different companies across multiple key indicators in AsciiDoc format.
 I> Company A:
 * Net income: $1,345,689
 * Revenue: $4,287,034
 * Employees: 1,502
 Company B:
 * Net income: $2,378,952
 * Revenue: $3,766,109
 * Employees: 3,450
 A> Here's an AsciiDoc table comparing financial data for two companies:

 .Comparison of financial data for two companies
 [%header, options="header:best-fit"]
 |===
 | Company   | Net Income (USD) | Revenue (USD) | Employees |
 |-----------|-----------------|---------------|----------|
 | Company A | 1,345,689       | 4,287,034     | 1,502    |
 | Company B | 2,378,952       | 3,766,109     | 3,450    |
 |===

 Q> Create an AsciiDoc table for a list of five retail stores and their respective locations, opening hours, and owner details.
 I> 
 A> This AsciiDoc table lists five retail stores along with their locations, opening hours, and owner details:

 .Table showing retail stores' information
 [%header, options="header:best-fit"]
 |===
 | Store                | Location          | Opening Hours   | Owner               |
 |----------------------|------------------|----------------|--------------------|
 | Amazon.com           | Online            | 24/7           | Jeff Bezos         |
 | Best Buy             | Worldwide         | 10 AM - 9 PM   | Corie Barry        |
 | IKEA                | Global            | 10 AM - 9 PM   | Jesper Brodin      |
 | Target               | US (various)      | 8 AM - 10 PM   | Brian Cornell      |
 | Walmart              | US (various)      | 24/7           | Doug McMillon     |
 |===

 This AsciiDoc table displays five retail stores with relevant information, including location, opening hours, and owner details.


 94% 94/100 [13:23<00:46,  7.72s/it]INFO 2024-06-26 21:28:22,199 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Construct an AsciiDoc table from the provided list of popular AI assistants, showcasing their release dates, creators, and parent companies.
 I> Popular AI Assistants:
 1. Siri (Oct 2011): Apple Inc.
 2. Google Assistant (May 2016): Google LLC
 3. Alexa (Nov 2014): Amazon.com, Inc.
 4. Cortana (Apr 2014): Microsoft Corporation
 5. Bixby (Mar 2017): Samsung Electronics Co., Ltd.
 A> Here is an AsciiDoc table regarding the popular AI assistants:

 .Popular AI Assistants with their Release Dates and Creators
 |===
 | AI Assistant   | Release Date (Year)      | Creator            | Parent Company    |
 |---------------|---------------------------|--------------------|------------------|
 | Siri          | 2011                      | Apple Inc.          | Apple Inc.        |
 | Google Assistant | 2016                     | Google LLC         | Alphabet Inc.    |
 | Alexa         | 2014                      | Amazon.com, Inc.    | Amazon.com, Inc.  |
 | Cortana       | 2014                      | Microsoft Corporation | Microsoft Corporation      |
 | Bixby         | 2017                      | Samsung Electronics Co., Ltd.| Samsung Electronics Co., Ltd.  |
 |===


 95% 95/100 [13:30<00:38,  7.61s/it]INFO 2024-06-26 21:28:29,326 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Extract column A values from the AsciiDoc table and display them as a simple list.
 I> [%header, cols="^ , ^"]
 |===
 | ^   | Column A | Column B   | ^  
 |------|---------|-----------|-----
 | Row  | Cell A1 | Cell B1   | Row 1
 | 1    | Cell A2 | Cell B2   | 2
 |------|---------|-----------|-----
 | Row 3 | Cell A3 | Cell B3   | Row 4
 | 4    | Cell A4 | Cell B4   | 5
 |===
 A> Column A values in the AsciiDoc table are:
 - Cell A1
 - Cell A2
 - Cell A3
 - Cell A4

 The extraction and conversion of the table into a list format allows for further analysis and manipulation of the data.

 Q> How would you modify an AsciiDoc table to add an additional column for data, such as URLs?
 I> 
 A> To add an additional column in an AsciiDoc table, say for URLs, just include a new column indicator in the header row, followed by subsequent rows containing the desired URLs. Here's an example for the case you provided earlier:

 .Popular programming languages with creators, release years, and official URLs
 [%header, cols="^ , ^ , ^*"]
 |===
 | Language      | Creator            | Release Year  | * URL
 |---------------|--------------------|--------------|--------------
 | C             | Dennis Ritchie      | 1972         | [C official website](https://www.iso.org/standard/22236.html)
 | C++           | Bjarne Stroustrup  | 1985         | [C++ official website](https://isocpp.org/)
 | Python        | Guido van Rossum   | 1991         | [Python official website](https://www.python.org/)
 | Java          | James Gosling      | 1995         | [Java official website](https://www.oracle.com/java/)
 | JavaScript     | Brendan Eich        | 1995         | [JavaScript official website](https://developer.mozilla.org/en-US/docs/Web/JavaScript)
 | Ruby          | Yukihiro 'Matz' Matsumoto  | 1995         | [Ruby official website](https://www.ruby-lang.org/en/)
 |===

 This way, an additional column containing the official websites URLs has been added, enhancing the table's informational value.


 97% 97/100 [13:44<00:22,  7.37s/it]INFO 2024-06-26 21:28:43,096 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> List the five most populated cities in the world with their respective populations in an AsciiDoc table using realistic data.
 I> 
 A> Here's an AsciiDoc table with the five most populated cities, along with their populations:

 .Top Five Most Populated Cities
 [%header]
 |===
 | City           | Population (Millions)
 | Tokyo         | 37.4               
 | Delhi         | 30.1               
 | Shanghai      | 27.0               
 | São Paulo     | 22.0               
 | Mumbai        | 20.7               
 |===

 Q> Generate an AsciiDoc table outlining the top ten largest tech companies by market capitalization. You should include the company name, ticker symbol, and market capitalization (in USD).
 I> 
 A> Here's an AsciiDoc table containing the top ten largest tech companies by market capitalization, as of December 2021:

 .Top Ten Largest Tech Companies by Market Capitalization
 [%header]
 |===
 | Company      | Ticker | Market Capitalization (USD)
 | Apple        | AAPL   | 2,456,258,000  
 | Microsoft    | MSFT   | 2,393,884,000  
 | Alphabet    | GOOGL  | 1,829,623,000  
 | Amazon       | AMZN   | 1,791,130,000  
 | Alibaba     | BABA   | 668,098,000    
 | Facebook     | FB     | 915,111,000    
 | Tesla       | TSLA   | 1,091,246,000  
 | Tencent     | TCEHY  | 625,263,000    
 | NVIDIA      | NVDA   | 532,184,000    
 | Berkshire Hathaway (Class B)   | BRK.B  | 644,845,000
 |===


 99% 99/100 [13:57<00:07,  7.07s/it]INFO 2024-06-26 21:28:55,990 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 INFO 2024-06-26 21:29:01,044 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->inference->quantitative->asciidoc->tables
 Q> Determine if a provided AsciiDoc table adequately describes a novel and its main characters, then give a brief evaluation based on the content.
 I> .Novel Description
 [%header]
 |===
 | Title                  | Main Character(s)
 | The Kite Runner        | Amir, Hassan                     
 | The Painted Veil       | Kitty Fane, Walter Fane         
 | Gone with the Wind    | Scarlett O'Hara, Rhett Butler    
 | Pride and Prejudice    | Elizabeth Bennet, Mr. Darcy      
 | The Catcher in the Rye  | Holden Caulfield                  
 |===
 A> The AsciiDoc table provided appears to be an adequate description of the novels and their main characters. It contains popular books and associated protagonists, and the format is clear and well-organized.

 Q> Estimate the time required to transform an existing table in a markdown format into an AsciiDoc table format based on the provided sample.
 I> .Markdown table
 | Title             | Author           | Genre      |
 |-------------------|-----------------|------------|
 | Pride and Prejudice | Jane Austen | Romance   |
 | The Great Gatsby   | F. Scott Fitzgerald | Drama  |
 | Jane Eyre          | Charlotte Bronte  | Gothic  |
 | Wuthering Heights | Emily Bronte    | Romance, Gothic |
 | The Catcher in the Rye | J.D. Salinger | Coming-of-age |
 A> Transforming a table similar to the provided sample from Markdown format into an AsciiDoc table format would take around 3-5 minutes, accounting for the need to change the header attributes and possibly alter other formatting aspects.


 101it [14:14,  7.50s/it]            
 101it [14:14,  8.46s/it]
 INFO 2024-06-26 21:29:12,836 generate_data.py:609: generate_data 101 instructions generated, 56 discarded due to format (see /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/inference/quantitative/asciidoc/tables/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_14_58.log), 0 discarded due to rouge score
 INFO 2024-06-26 21:29:12,836 generate_data.py:613: generate_data Generation took 854.29s
 Completed 124.1 KiB/314.5 KiB (718.0 KiB/s) with 4 file(s) remaining
 upload: ../outputtopush/train_Mixtral-8x7B-Instruct-v0_2024-06-26T21_14_58.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/inference/quantitative/asciidoc/tables/train_Mixtral-8x7B-Instruct-v0_2024-06-26T21_14_58.jsonl
 Completed 124.1 KiB/314.5 KiB (718.0 KiB/s) with 3 file(s) remaining
 Completed 179.5 KiB/314.5 KiB (852.2 KiB/s) with 3 file(s) remaining
 upload: ../outputtopush/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_14_58.log to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/inference/quantitative/asciidoc/tables/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_14_58.log
 Completed 179.5 KiB/314.5 KiB (852.2 KiB/s) with 2 file(s) remaining
 Completed 309.0 KiB/314.5 KiB (1.2 MiB/s) with 2 file(s) remaining  
 upload: ../outputtopush/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T21_14_58.json to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/inference/quantitative/asciidoc/tables/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T21_14_58.json
 Completed 309.0 KiB/314.5 KiB (1.2 MiB/s) with 1 file(s) remaining
 Completed 314.5 KiB/314.5 KiB (1.1 MiB/s) with 1 file(s) remaining
 upload: ../outputtopush/test_Mixtral-8x7B-Instruct-v0_2024-06-26T21_14_58.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/inference/quantitative/asciidoc/tables/test_Mixtral-8x7B-Instruct-v0_2024-06-26T21_14_58.jsonl
 compositional_skills/STEM/math/area/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/STEM/math/area/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/STEM/math/area --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T21:29:15Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/STEM/math/area/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 21:29:23,531 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area

  0% 0/100 [00:02<?, ?it/s]INFO 2024-06-26 21:29:26,465 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area

  0% 0/100 [00:06<?, ?it/s]INFO 2024-06-26 21:29:29,616 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area

  0% 0/100 [00:07<?, ?it/s]INFO 2024-06-26 21:29:31,233 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area

  0% 0/100 [00:10<?, ?it/s]INFO 2024-06-26 21:29:34,040 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area

  0% 0/100 [00:14<?, ?it/s]INFO 2024-06-26 21:29:37,805 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area

  0% 0/100 [00:16<?, ?it/s]INFO 2024-06-26 21:29:39,904 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Provide the formula to find the area for a circle and define each symbol used.
 I> 
 A> The formula to find the area of a circle is A = πr², where:
 - A is the area of the circle
 - π (pi) is a mathematical constant with an approximate value of 3.14159
 - r is the radius of the circle (distance from the center of the circle to its perimeter).
 Let me know if you have any other questions or need further clarification.

 Q> If the area of a circle is 50 square inches, what is the diameter of the circle?
 I> 
 A> To find the diameter of a circle given its area, you'd first solve for the radius using the formula πr², where r is the radius and π is approximately equal to 3.14159. In this case, the area given is 50 square inches. So, the radius would be sqrt((50 square inches) / π) ≈ 3.18 inches. Therefore, the diameter of the circle would be 2\*Radius = 2\*3.18 ≈ 6.36 inches. Let me know if you have any other questions or need assistance with something else.


  2% 2/100 [00:26<08:33,  5.24s/it]INFO 2024-06-26 21:29:50,393 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Consider a circular garden with a 7-meter diameter. Calculate its area.
 I> 
 A> To calculate the area of the circular garden, we need to use the formula πr², where r is the radius of the garden. Given that the diameter is 7 meters, the radius is half of it: r = 7 m / 2 = 3.5 m. Therefore, the area is π \* (3.5 m)² = approximately 38.49 square meters.

 Q> Explain to me how the formula for area of a circle is derived.
 I> 
 A> The formula for the area of a circle is derived from the concept of integrating infinitesimal slices of a circle. The integrated area of a circle is represented as the sum of the infinite number of slices within the radius. Mathematically, this is expressed as: A = ∫₀ʳ 2πr \* dr, where r represents the radius of the circle. Solving the integral results in the area formula A = πr².


  4% 4/100 [00:36<08:12,  5.13s/it]INFO 2024-06-26 21:30:00,488 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 INFO 2024-06-26 21:30:03,740 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Illustrate an example in which you calculate the area of a circle using 3.14 for π.
 I> The radius of the circle is 6 centimeters.
 A> To calculate the area of a circle with a given radius and using 3.14 for π, follow this example: radius = 6 cm. Apply the formula A = πr² to obtain the result A = 3.14 \* (6 cm)² = approximately 113.1 cubic centimeters. Keep in mind that this value is just an approximation, while the actual value would result in a more accurate area if computed with the exact constant for π.

 Q> Show me how to code a Python function that calculates the area of a circle, given its radius.
 I> 
 A> To define a Python function that calculates the area of a circle, apply this example:

 ```python
 import math

 def circle_area(radius):
    """
    Function to calculate the area of a circle.
    :param radius: float or int
    :return: float
    """
    return math.pi * (radius ** 2)
 ```

 To use this function, simply input the radius value; it will return the calculated area as a float.


  6% 6/100 [00:50<09:20,  5.97s/it]INFO 2024-06-26 21:30:14,417 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 INFO 2024-06-26 21:30:17,210 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> What is the area of a circle with a radius of 10 centimeters, and how is this result derived?
 I> 
 A> The area of a circle with a radius of 10 centimeters is calculated using the formula πr², where r is the radius of the circle. In this example, r equals 10 cm; hence, the area will be π \* (10 cm)² = approximately 314 square centimeters.

 Q> Explain the concept of π and its role in calculating the area of a circle.
 I> 
 A> π (pi) is a mathematical constant representing the ratio of a circle's circumference to its diameter. It is approximately equal to 3.14159. When calculating the area of a circle, π is multiplied by the square of the radius (πr²) because the circle's area corresponds to the space enclosed by its circumference. This method effectively distributes the circumference over the circle while ensuring proper coverage.


  8% 8/100 [01:03<09:25,  6.15s/it]INFO 2024-06-26 21:30:27,274 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> When presented with a circle's diameter, how can you determine its area?
 I> 
 A> To find the area of a circle given its diameter, first determine the radius by dividing the diameter by 2. Then, use the formula A = πr², where A is the area and r is the radius. Let me know if you need more information or have other questions!

 Q> Describe the relationship between the area of a circle and its circumference.
 I> 
 A> The relationship between a circle's area and its circumference is that they both depend on the square of the radius. The circumference is given by C = 2πr, and the area is given by A = πr². As the radius squares, increasing the radius will increase both the circumference and the area. Let me know if you have any other questions or need further clarification.


 10% 10/100 [01:13<08:31,  5.69s/it]INFO 2024-06-26 21:30:37,018 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Imagine a circular pizza with a diameter of 14 inches. Approximately what would be the area occupied by one slice, assuming it's divided into eight equal parts?
 I> Assume the pizza has a uniform thickness and is divided into eight equal slices.
 A> First, determine the radius, which is half of the diameter: 14 inches / 2 = 7 inches. Then, calculate the area of the entire pizza: A = πr² = π \* (7 inches)² = approximately 154 square inches. Finally, divide this value by the number of slices, 8, to find the area of one slice: 154 square inches / 8 = approximately 19.25 square inches.


 11% 11/100 [01:18<08:23,  5.65s/it]INFO 2024-06-26 21:30:42,528 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Explain how to find the area of a circle.
 I> 
 A> To find the area of a circle, you can use the formula πr², where r is the circle's radius. Multiply the radius by itself and then multiply that result by π, which is a mathematical constant approximately equal to 3.14159. For example, a circle with a radius of 3 units would have an area of 3² \* π ≈ 28.27 square units. Let me know if you have any other questions or need assistance with something else.

 Q> Calculate the area of a circle with a circumference of 12.56 inches.
 I> 
 A> The formula for calculating the area of a circle from its circumference is not straightforward, since different circles can share the same circumference and have different areas. This is possible because the relationship between the two variables is not linear. The formula for circumference is C = 2πr, and if we solve this equation for r we get r = C / (2π). Given C = 12.56 inches, r = 12.56 / (2π) ≈ 2 inches. Therefore, the area would be π \* (2 inches)² = approximately 12.56 square inches. Let me know if you have any other questions or need assistance with something else.


 13% 13/100 [01:30<08:07,  5.60s/it]INFO 2024-06-26 21:30:53,562 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Illustrate the formula for calculating the area of a circle with an example given a radius of 5 units.
 I> 
 A> The formula for calculating the area of a circle is πr², where r is the circle's radius. Let's consider r as 5 units; then, the area would be π \* (5 units)² = 78.54 square units. This means that the circle with the specified radius covers an area of 78.54 square units.

 Q> Can you explain how to calculate the area of a circle?
 I> 
 A> Certainly! To compute the area of a circle, use the formula πr², where r denotes the circle's radius, and π is a constant approximately equal to 3.14159265. Simply square the radius value and multiply it by π to get the result.


 15% 15/100 [01:39<07:35,  5.36s/it]INFO 2024-06-26 21:31:03,355 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Given a circle with an area of 50 square inches, what is the radius?
 I> 
 A> To find the radius of a circle with a given area, you need to rearrange the formula A = πr² and solve for r. In this case, A = 50 in², and π is approximately 3.14159. Solving for r, you get r² = (A / π), so r = sqrt((A / π)) = sqrt((50 in² / 3.14159)) ≈ 5.1 inches. Therefore, the radius is approximately 5.1 inches. Let me know if you have any other questions or need further clarification.

 Q> Explain the difference in the method used to calculate the area of a circle compared to a square.
 I> 
 A> The formula to calculate the area of a circle is A = πr², where r is the radius of the circle. This formula uses the square of the radius because the circle can be approximated by an inscribed square with side length equal to the diameter, so the area of the square is side length squared. However, for the circle, the actual area of the circle is smaller than the square's area. To compensate for this difference, a constant (π) is multiplied, giving a more accurate result. Let me know if you have any other questions or need assistance with something else.


 17% 17/100 [01:50<07:29,  5.42s/it]INFO 2024-06-26 21:31:14,425 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> In a geometric design project, a circle with an area of 38.48 square inches is required. What should be the radius of this circle? (Use the approximation π ≈ 3.14159 and solve to two decimal places.)
 I> 
 A> First, we need to rearrange the area formula to solve for the radius. The rearranged formula is r = √(A/π). Now, substitute 38.48 square inches for A and 3.14159 for π: r = √(38.48 / 3.14159) ≈ 3.25 inches.

 Q> Given a cylindrical tank with a height of 15 feet and a base area of 49.09 square feet, what is its total volume (π ≈ 3.14159)?
 I> 
 A> The volume of a cylinder is given by the formula V = πr²h. In this case, the base area is provided, and the radius can be found by taking the square root of the given base area: r = √(49.09) ≈ 7 feet. Now, substituting given values and the approximation π ≈ 3.14159, we calculate the volume as V = 3.14159 \* (7 feet)² \* 15 feet ≈ 2,240.99 cubic feet.


 19% 19/100 [02:02<07:25,  5.50s/it]INFO 2024-06-26 21:31:25,763 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> If the radius of a circle is 6 cm, what is its area?
 I> 
 A> Given a circle with a radius of 6 cm, the area can be calculated as A = πr², where r is the radius and π (pi) is a mathematical constant. Plugging in 6 cm for r, we get A = π(6 cm)², which is equal to approximately 36π square centimeters, or about 113.097 square centimeters. Let me know if you have any other questions or need assistance with something else.

 Q> Explain how to compute the area of a circle using its diameter.
 I> 
 A> To find the area of a circle using its diameter, we first need to calculate the radius. The radius is half the diameter, so it's simply a matter of dividing the diameter by 2. Then we can use the standard formula for calculating the area of a circle, A = πr². Using the diameter in the radius calculation gives us A = π(diameter / 2)². This allows us to calculate the area using the diameter directly. For example, if the diameter is 12 cm, the radius would be 6 cm and the area would be approximately 113.097 square centimeters (A = π(6 cm)²). Let me know if you have any other questions or need assistance with something else.


 21% 21/100 [02:13<07:14,  5.50s/it]INFO 2024-06-26 21:31:36,745 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Give an example of how the formula of a circle's area differs from that of a square's area.
 I> The radius of the circle and the side length of the square are both 5 units.
 A> Let's calculate the area for both figures using their respective formulas. The circle area formula is A\_circle = πr² and, for a square, A\_square = s², where r = radius and s = side length. For the circle, A\_circle = π(5)^2 = approximately 78.5 square units. For the square, A\_square = (5)^2 = 25 square units. As you can see, the area of the circle is larger due to its shape being more spread out than the square.

 Q> How does increasing the radius of a circle affect its area?
 I> Change the circle's radius from 4 units to 6 units.
 A> As the radius of a circle increases, so does its area. In this example, we are increasing the radius from 4 units to 6 units. If we apply the formula A = πr², we can determine the new area. So, the area of the circle with a radius of 4 units is A1 = π(4)^2 = approximately 50.27 square units, whereas the area of the circle with a radius of 6 units is A2 = π(6)^2 = approximately 113.1 square units. A2 is larger than A1 due to the increased radius.


 23% 23/100 [02:24<07:05,  5.52s/it]INFO 2024-06-26 21:31:47,893 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> How do you calculate the area of a circle? Provide a general formula.
 I> 
 A> The area of a circle can be calculated using the formula πr², where r is the radius of the circle. To find the area, simply square the radius and multiply the result by π.

 Q> An online store sells circular tables with a 2-feet diameter. Help me estimate the area for this size.
 I> 
 A> The area of a circular table with a 2-feet diameter can be estimated by calculating the square feet within the table's dimensions. First, we need to find the radius: r = 2 feet / 2 = 1 foot. Using the formula for the area of a circle (πr²), the result is π \* (1 foot)² = approximately 3.14 square feet.


 25% 25/100 [02:34<06:40,  5.35s/it]INFO 2024-06-26 21:31:57,799 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 INFO 2024-06-26 21:32:02,051 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Derive the formula for computing the area of a circle from first principles.
 I> 
 A> To derive the formula for the area of a circle, we can use an approximation method. Imagine a circle being composed of an increasing number of very thin triangles inside. With the central angle of each triangle becoming smaller, the triangles more closely resemble straight lines. The sum of the lengths of these lines converges to the circle's circumference. By considering the limiting case, we can state that the perimeter of the polygon is equal to the circle's circumference. Now, if we decrease the number of triangles and increase the number of sides, the polygon approaches the shape of the circle. The total area of the triangles approximates the area of the circle. This leads us to the understanding that if we divide the circumference of the circle by its diameter, we will find a constant value. This constant is π, so C = πd. By increasing the number of sides, the function will eventually result in πr². This is the area of the circle. Let me know if you have any other questions or need assistance with something else.

 Q> Provide a real-world application example for calculating the area of a circle.
 I> 
 A> A common practical application for calculating the area of a circle is in construction, where circular foundations are laid. If the excavation team needs to dig a circular area for a building's foundation, a precise calculation of the cross-sectional area will be necessary to calculate the required volume of soil to be removed. Similarly, estimating the required volume of concrete and other materials for building the foundation strongly depends on accurate area calculation. By using the formula πr², approximately 3.14 times the square of the radius, the area can be calculated easily. This allows a smooth and precise construction process, avoiding delays and saving costs. Let me know if you have any other questions or need assistance with something else.


 27% 27/100 [02:50<07:31,  6.19s/it]INFO 2024-06-26 21:32:14,023 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> How would you determine the area for a circle with a radius of 8 units?
 I> 
 A> To find the area for a circle with a radius of 8 units, apply the formula πr², resulting in π \* (8 units)², which is equivalent to approximately 201.06 square units.

 Q> Provide a real-life situation where you need to compute the area of a circle.
 I> 
 A> Imagine you're a landscaper designing a round patio in a client's backyard. To calculate the necessary materials, you'd compute the area using the formula πr², where "r" represents the circle's radius, equal to half the length of the diameter.


 29% 29/100 [02:59<06:48,  5.75s/it]INFO 2024-06-26 21:32:23,533 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> If the radius of a circle is 3 inches, what will be its area?
 I> 
 A> The area of a circle can be calculated using the formula A = πr². So if the radius is 3 inches, the area will be A = π(3²) = 9π square inches, or approximately 28.27 square inches.

 Q> Write a python function to calculate the area of a circle with radius as an input.
 I> 
 A> Here is a Python function to calculate the area of a circle, given the radius as an input:

 ```python
 import math
 def find_circle_area(radius):
  area = math.pi * (radius ** 2)
  return area
 
 # Example usage
 print(find_circle_area(5))
 ```


 31% 31/100 [03:09<06:18,  5.49s/it]INFO 2024-06-26 21:32:33,292 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Tell me the formula for the area of a circle and provide its units.
 I> 
 A> The formula for the area of a circle is A = πr², where r denotes the radius. The area can be measured in square units such as square inches, square feet, square meters, or square centimeters.

 Q> Suppose a circle's diameter is 10 inches. What would be the area of this circle?
 I> 
 A> For a circle with a diameter of 10 inches, its radius would be 5 inches. Consequently, the area can be determined using A = πr², where r is the radius: π \* (5 inches)². This results in an area of approximately 78.54 square inches.


 33% 33/100 [03:19<05:54,  5.29s/it]INFO 2024-06-26 21:32:42,977 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 INFO 2024-06-26 21:32:45,753 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Could you show me the calculation for finding the area of a circle given a radius of 5.5 meters?
 I> 
 A> Certainly! For a circle with a radius of 5.5 meters, the area is calculated using the formula A = πr². Therefore, the area is A = π \* (5.5 m)², yielding approximately 95.03 square meters.

 Q> Give me an example of calculating the area of a circle when the radius is 2.2 yards.
 I> 
 A> When the radius is 2.2 yards, you can calculate the area using the formula A = πr². Plugging in 2.2 yards, we get A = π \* (2.2 yards)². This results in an area of approximately 15.2 square yards.


 35% 35/100 [03:31<06:02,  5.58s/it]INFO 2024-06-26 21:32:55,465 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 INFO 2024-06-26 21:32:58,334 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> How would you determine the area of a circle with a radius of 7 cm?
 I> radius = 7 cm
 A> To calculate the area of the circle with a radius of 7 cm, apply the formula A = πr². Here, r equals 7 cm. Substitute the radius value into the formula and calculate the area as follows: A = π ∗ (7 cm)² ≈ 153.94 cm².

 Q> Describe the concept of pi and its relation to the area of a circle.
 I> 
 A> Pi is a mathematical constant approximately equal to 3.14159. It represents the ratio of a circle's circumference to its diameter. In decimal format, pi is an irrational number with an endless series of non-repeating digits. Pi can also be represented as π, and it is used in several mathematical equations related to circles. The area of a circle consists of the product of pi and the square of the circle's radius. Mathematically, the area of a circle is expressed as A = πr².


 37% 37/100 [03:45<06:10,  5.88s/it]INFO 2024-06-26 21:33:08,587 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Describe the significance of pi in finding the area of a circle.
 I> 
 A> Pi is a critical constant in calculating the area of a circle. It represents the ratio between the circumference and the diameter of any circle, and its value is approximately 3.14159. When used in the area formula, πr², the pi multiplier allows us to represent the gap between the circle's edge and the square with the same diameter more accurately.

 Q> Explain how we can determine the radius of a circle given its area.
 I> Assume a circle has an area of 154 square inches.
 A> To find a circle's radius (r) given its area (A), you will need to rearrange the area formula: A = πr². In this case, A equals 154 square inches. Start by dividing both sides by π, which gives you: r² = A / π. Now, we know A and π, resulting in r² = 154 / π. Compute the square root of both sides to isolate r, r = √(A / π). This will give you the radius, √(154 / π), which is approximately 7 inches.


 39% 39/100 [03:55<05:47,  5.69s/it]INFO 2024-06-26 21:33:19,112 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> How does the value of the radius impact the area of a circle?
 I> 
 A> The radius of a circle plays a significant role in calculating its area since the formula involves the square of the radius (A = πr²). Therefore, an increase or decrease in the radius causes a more substantial shift in the area. For example, doubling the radius would quadruple the area, and halving the radius would reduce the area to a quarter of its original value.

 Q> Can you provide an example showing how to calculate the area of a circle?
 I> 
 A> Sure. Consider a circle with a radius of 3 inches. By applying the formula A = πr², we get π \* (3 inches)², resulting in approximately 28.27 square inches for the area.


 41% 41/100 [04:05<05:21,  5.44s/it]INFO 2024-06-26 21:33:28,852 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> How would you approximate the area occupied by a circular pen with a radius of 1.5 inches? Note that π cannot be precisely calculated, so let's use 22/7 as an approximation.
 I> 
 A> To estimate the area, first, calculate the square of the radius: 1.5 inches \* 1.5 inches = 2.25 square inches. Then, use the approximation of π as 22/7: area = (22/7) \* 2.25 square inches ≈ 7.0667 square inches.

 Q> For a circle with a diameter of 11 meters, what identity could be used for finding the area?
 I> 
 A> Given a circle with a diameter of 11 meters, you must first determine its radius, which is half of the diameter: radius = 11 meters / 2 = 5.5 meters. The area of a circle can be calculated using the formula: A = πr², where A is the area and r is the radius.


 43% 43/100 [04:15<05:05,  5.37s/it]INFO 2024-06-26 21:33:39,231 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 INFO 2024-06-26 21:33:42,863 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Suppose a circle has an area of 78.54 square units, what is the radius of that circle?
 I> **
 Area: 78.54 square units
 A> **
 The radius of the circle with an area of 78.54 square units is approximately 4.5 units (rounded to one decimal place). Given the area formula: A = πr², the equation can be rearranged to find the radius: r = sqrt(A/π), then r = sqrt(78.54/π) = 4.503... ≈ 4.5 units.


 44% 44/100 [04:25<05:49,  6.23s/it]INFO 2024-06-26 21:33:49,492 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> What is the pattern in the calculation of the area of a circle compared to an n-sided regular polygon?
 I> 
 A> When calculating the area of a circle and an n-sided regular polygon, both depend on the square of the length of their sides or the radius. The circle formula is A = πr², and for regular polygons, an approximation is used, such as A = (1/4)nr²sin(2π/n). The formula for the regular polygon converges to the area of the circle as the number of sides n increases.

 Q> Take a real-life example and estimate the area of a circle in it, like a dinner plate or a hula hoop.
 I> Consider a circular dinner plate with a diameter of 25 cm.
 A> Let's calculate the area of the dinner plate based on the provided diameter. The radius would be half of this, r = 25/2 = 12.5 cm. The area of the circle would be A = πr² = π(12.5)². That is approximately equivalent to 491 square centimeters.


 46% 46/100 [04:36<05:17,  5.89s/it]INFO 2024-06-26 21:33:59,902 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Explain the method for finding the area of a circle.
 I> 
 A> The area of a circle can be found by using the formula: A = πr², where 'A' represents the area and 'r' is the circle's radius. This formula calculates the area by taking the square of the radius and then multiplying it by pi (π).

 Q> Provide the area of a circle in terms of its diameter.
 I> 
 A> If the diameter of a circle is known instead of its radius, you can calculate the area using the formula: A = π(d/2)², where 'A' is the area of the circle, and 'd' is the diameter. This formula calculates the area by first dividing the diameter by 2 to get the radius, then squaring that value and multiplying by pi (π).


 48% 48/100 [04:46<04:49,  5.57s/it]INFO 2024-06-26 21:34:09,724 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Consider a circle with a radius of 5 units. What is its area?
 I> 
 A> The area of a circle with a radius of 5 units is calculated as π multiplied by the square of the radius. This results in an area of 78.54 square units (rounded to two decimal places).

 Q> How does the area of a circle change when you double the radius? Demonstrate with a concrete example.
 I> 
 A> When the radius of a circle doubles, its area increases by a factor of 4. For example, if a circle with a radius of 3 units has an area of about 28.27 square units, a circle with a radius 6 units will have an area of approximately 113.10 square units.


 50% 50/100 [04:55<04:26,  5.33s/it]INFO 2024-06-26 21:34:19,328 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> What is the difference between using the radius and diameter in calculating the area of a circle?
 I> 
 A> When calculating the area of a circle, the radius is typically used. The formula is A = πr². However, it can also be done using the diameter. First, divide the diameter by 2 to obtain the radius. Next, calculate the area using the radius. Although there are two steps involved, both methods are based on the same π value and provide correct results.

 Q> Provide an example to demonstrate the connection between the circle's diameter and its area.
 I> 
 A> Sure! Consider a circle with a diameter of 10 units. The radius is half this value, i.e., 5 units. Using the standard formula A = πr², we can find the area by substituting r = 5. This results in an area of A = π \* 5², or approximately 78.5 square units. Thus, the area of a circle is influenced by its diameter (which relates to the radius) as well as π.


 52% 52/100 [05:06<04:13,  5.29s/it]INFO 2024-06-26 21:34:29,708 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Can you demonstrate how to apply the area formula of a circle to an example with a radius of 3.5 cm?
 I> Calculate the area of a circle with a radius of 3.5 cm.
 A> Certainly! To calculate the area of a circle with a radius of 3.5 cm, use the formula A = πr². Given r = 3.5 cm, square the radius: (3.5 cm)² = 12.25 cm². Now multiply the result by π: A = 12.25 cm² × π ≈ 38.48 cm². Therefore, a circle with a radius of 3.5 cm has an area of approximately 38.48 square centimeters.

 Q> Describe a scenario where finding the area of a circle is useful and give an example of the radius in that context.
 I> 
 A> Finding the area of a circle is useful in many situation, such as computing the amount of paint required to cover a circular wall. Suppose a round wall has a radius of 6 feet. To calculate the amount of paint needed, first find the area: A = πr² = π(6 feet)² = 36π square feet, which is approximately 113.1 square feet. With this information, you can determine the optimal quantity of paint for the project.


 54% 54/100 [05:16<04:04,  5.31s/it]INFO 2024-06-26 21:34:40,412 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Suppose the area of a circle is 50 square units. What is the radius?
 I> 
 A> To find the radius, given the area of a circle, you can use the formula for the area (A = πr²). Isolate the radius (r) by dividing both sides by π and taking the square root. In this case, solving for r requires finding the square root of 50/π, or approximately 3.16 units.

 Q> What are the steps needed to calculate the area of a circle with a radius of 6 cm?
 I> 
 A> To calculate the area of a circle when given the radius, use the formula A = πr², where r is the radius. For a circle with a radius of 6 cm, the area would be π \* (6^2) = 36π, which is around 113.1 cm².


 56% 56/100 [05:26<03:48,  5.20s/it]INFO 2024-06-26 21:34:50,324 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Calculate the area of a circle given a diameter of 10 feet.
 I> 
 A> To find the area of a circle when given its diameter, you can first find the radius, which is half of the diameter. In this case, the radius is 10 feet / 2 = 5 feet. Then, use the formula πr² to find the area. So, the area would be π \* (5 ft)² = approximately 78.54 square feet. Let me know if you have any other questions or need assistance with something else.

 Q> What is the formula for finding the area of a circle?
 I> 
 A> The formula for finding the area of a circle is πr², where r is the radius of the circle. To use this formula, simply square the radius (multiply it by itself), then multiply the result by π, which is a mathematical constant approximately equal to 3.14159. For example, the area of a circle with a radius of 4 units would be π \* (4 u)² = approximately 50.27 square units. Let me know if you have any other questions or need assistance with something else.


 58% 58/100 [05:37<03:39,  5.22s/it]INFO 2024-06-26 21:35:00,839 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> If you were to create a circular floor mat with an area of 10 square feet, what would be the radius required?
 I> 
 A> To find the radius needed to create a circular floor mat with an area of 10 square feet, we'll use the formula for the area of a circle: A = πr², where A represents the area, and r is the radius. Given that A = 10 sq ft, we need to solve for r. First, divide the area by π to get (10 sq ft) ÷ π ≈ 3.18 sq ft. Now, take the square root of 3.18 to find r. This should result in approximately 1.78 feet.

 Q> How would you determine the area of a circle with a circumference of 20π inches?
 I> 
 A> To calculate the area of a circle provided its circumference, you can use the circumference value to find the diameter, as the circumference is calculated as C = 2πr or C = πd. Given C = 20π inches, either C = 2π(5) or C = π(10). Once you have the diameter, divide it by 2 to get the radius, and then use the formula A = πr² to find the area. In this case, A = π(5)², with A being the area. This results in A = 25π sq in.


 60% 60/100 [05:48<03:32,  5.31s/it]INFO 2024-06-26 21:35:11,873 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> What is the formula to determine the area of a circle?
 I> 
 A> The formula for calculating the area of a circle is A = πr², where A represents the area and r denotes the radius of the circle. In this formula, π (pronounced "pi") is a mathematical constant representing a little more than 3.14159, which can be approximated to 3.14 when necessary.

 Q> Explain the relationship between the area of a circle and the radius?
 I> 
 A> The area of a circle is directly proportional to the square of its radius. A larger radius corresponds to a larger area, while a smaller radius results in less area. This relationship is expressed mathematically as A = πr², providing a foundation for understanding and calculating the area of any circle.


 62% 62/100 [05:58<03:16,  5.18s/it]INFO 2024-06-26 21:35:21,668 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 INFO 2024-06-26 21:35:24,090 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Prompt the assistant to calculate the area of a circle with a radius of 5 units.
 I> Circle radius: 5 units
 A> Given that the radius of the circle is 5 units, the formula to find its area is πr², where r is the radius. Plug in the radius value: π (5)². The result is approximately 78.54 units².


 63% 63/100 [06:05<03:25,  5.55s/it]INFO 2024-06-26 21:35:28,906 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Explain to me the relationship between the area of a circle and its diameter.
 I> 
 A> The relationship between the area of a circle and its diameter stems from the radius, since the diameter is twice its length. First, find the radius by dividing the diameter by 2, then apply the formula for the area: A = πr², where A is the area and r is the radius.

 Q> In your own words, describe the process for finding the area of a circle, using a radius of 10 units as an example.
 I> 
 A> To find the area given a circle with a radius of 10 units, we can use the formula A = πr², where A represents the area and r is the radius. In this case, we have r = 10 units, so A = π \* (10 units)², which is equivalent to approximately 314.16 square units.


 65% 65/100 [06:15<03:07,  5.35s/it]INFO 2024-06-26 21:35:38,854 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Assume there is a circular garden with an area of 226.19 square meters. What would be the radius of this garden?
 I> 
 A> To determine the radius of a circular garden with an area of 226.19 square meters, we'll apply the formula for the area of a circle, A = πr². First, we need to find the radius (r) using the given area (A = 226.19 m²). Divide the area by π to get a radius of 36 meters (since 226.19 ÷ π ≈ 36).

 Q> Could you provide and explain an example of approximating the area of a circle?
 I> 
 A> An example of approximating the area of a circle is using inscribed or circumscribed polygons. Suppose we have a circle with a radius of 5 centimeters. We could calculate the area of the circle by drawing a square with sides tangent to the circle. The side length of the square is 10 centimeters. The area of the square is 100 square centimeters. This value is an approximation of the circle's area. By increasing the number of sides, the approximation becomes more accurate.


 67% 67/100 [06:25<02:55,  5.32s/it]INFO 2024-06-26 21:35:49,343 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Given a circle with a radius of 7 inches, calculate its area.
 I> radius = 7 inches
 A> The area of the circle with a radius of 7 inches is π \* (7 in)² = approximately 153.937 square inches.

 Q> A circular garden has a diameter of 25 feet. What is its area?
 I> 
 A> The area of the circular garden is π \* (25 ft / 2)² = approximately 490.87 square feet.


 69% 69/100 [06:34<02:36,  5.06s/it]INFO 2024-06-26 21:35:58,318 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> How does the area of a circle differ from that of a square with the same perimeter?
 I> 
 A> For the same perimeter, the area of a circle will always be larger than a square. This results from the distribution of the circle's circumference over its surface area, making better use of the given perimeter compared to the square's side length.

 Q> Compare the area of a circle with a radius of 6 to one with a diameter of 10.
 I> 
 A> The area of a circle depends solely on its radius. A circle with a radius of 6 has an area of π \* (6)², whereas it is common to assume that a circle with a diameter of 10 has a radius of 5. Therefore, the area of the second circle would be π \* (5)². It is essential to use the correct value for radius, regardless of the available diameter, to accurately determine the area.


 71% 71/100 [06:44<02:25,  5.00s/it]INFO 2024-06-26 21:36:08,078 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Calculate the area of a circle with a diameter of 15 centimeters. (Use the approximation π ≈ 3.14159 and round your answer to one decimal place.)
 I> 
 A> To find the area of a circle with a diameter of 15 centimeters, first calculate its radius: r = diameter/2 = 15/2 = 7.5 cm. Now apply the area formula, A = πr², with 3.14159 as the approximation for π: A = 3.14159 * (7.5)². The result is approximately 176.71 cubic centimeters when rounded to one decimal place.

 Q> Suppose the area of a circular garden is 196π square feet. What is the radius and diameter of the garden?
 I> 
 A> If the area of a circular garden is 196π square feet, then its radius (r) is the square root of that area divided by π. In this case, r = √(196π/π) = 14 feet. Therefore, the diameter, equal to twice the radius, is 14 \* 2 = 28 feet.


 73% 73/100 [06:55<02:17,  5.09s/it]INFO 2024-06-26 21:36:18,635 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Find the area of a circle in terms of its diameter, which measures 16 feet.
 I> diameter = 16 feet
 A> Given a circle with a diameter of 16 feet, the radius is half of that value, so r = 16 feet / 2 = 8 feet. The area of the circle is calculated as πr², which results in π \* (8 feet)² = approximately 201.06 square feet.

 Q> What should the length of the side of a square be if its area is to be equal to that of a circle with a radius of 4 meters?
 I> 
 A> The area of a circle is given by πr², where r is the radius. For a radius of 4 meters, the area is equal to π \* (4 meters)² = approximately 50.27 square meters. To match this area, the side length of a square can be found by taking the square root of the area, resulting in a side length of approximately 7.07 meters.


 75% 75/100 [07:05<02:06,  5.08s/it]INFO 2024-06-26 21:36:28,735 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 INFO 2024-06-26 21:36:31,245 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 INFO 2024-06-26 21:36:34,498 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 INFO 2024-06-26 21:36:37,427 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Explain the concept of π (pi) and its significance in determining the area of a circle.
 I> 
 A> In mathematics, pi (π) represents the ratio of a circle's circumference to its diameter. It's approximately equal to 3.14159, but the digits can continue indefinitely. The significance of pi in determining the area of a circle is that it acts as a conversion factor for converting the radius to the units of area. Calculating the area involves multiplying the square of the radius by pi. By using pi, we can find the areas of circles regardless of their size, making this constant crucial for all circular objects.

 Q> Describe the relationship between the diameter and area of a circle in a single sentence.
 I> 
 A> The relationship between the diameter and area of a circle is that, for a given diameter, the area grows proportionately to the square of the diameter. This is due to the formula Area = π * (Diameter / 2)², where π is a constant.


 77% 77/100 [07:23<02:26,  6.37s/it]INFO 2024-06-26 21:36:47,439 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Given a circle with a diameter of 14 units, determine the area.
 I> Diameter: 14 units
 A> First, we need to find the radius of the circle, which is half the diameter. In this case, r = 14/2 = 7 units. To determine the area of the circle using radius, apply the formula: A = πr². Substituting r, we get A = π(7)² = 49π square units.


 78% 78/100 [07:34<02:35,  7.05s/it]INFO 2024-06-26 21:36:57,589 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 INFO 2024-06-26 21:37:01,625 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Explain how to calculate the area of a circle step by step.
 I> 
 A> To calculate the area of a circle, follow these steps: (1) Measure the diameter or radius, (2) compute the radius if you measured the diameter, (3) square the radius value, and finally (4) multiply the squared radius by π.

 Q> Consider a circular treehouse with a 22-foot diameter. Calculate a rough estimate of its area using 3.14 as the value of π.
 I> 
 A> To approximate the area of the circular treehouse with π equal to 3.14, first find the radius by dividing the diameter by 2. That is, 22 feet / 2 = 11 feet. Next, square the radius and multiply it by 3.14: (11 ft)² \* 3.14 ≈ 380.12 square feet.


 80% 80/100 [07:47<02:20,  7.01s/it]INFO 2024-06-26 21:37:11,441 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Imagine a circular garden with a diameter of 24 feet. What is the area it covers?
 I> radius = 12 feet
 A> The area of the circular garden is approximately 452.39 square feet (A = π(radius)²). This is calculated by first finding the radius, which in this case is 12 feet, and then using the formula for the area of a circle (A = πr²). The square feet unit represents the area the garden occupies within its circumference. Let me know if you need more real-life examples or have other questions on this topic.

 Q> Differentiate between the concept of circumference and area in the context of circles.
 I> 
 A> Circumference and area are two different circle measurements. The circumference is the perimeter of a circle and describes how far you must travel to go around it completely. It is calculated using the formula C = 2πr, where r represents the radius. In contrast, the area describes how much space is enclosed within the circle. It is calculated using the formula A = πr². For a visual aid and further understanding, I suggest searching for images comparing circle circumference and area in real-world examples.


 82% 82/100 [07:58<01:55,  6.43s/it]INFO 2024-06-26 21:37:21,908 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Can you tell me the area of a circle with a circumference of 22 units (assuming π as approximately 3.14)?
 I> 
 A> Sure! With a circumference of 22 units, you can compute the radius using C = 2πr, giving us r ≈ 22 / (2 × 3.14), which is r ≈ 3.45 units. The formula to find the area of a circle is A = πr², so the area would be A ≈ 3.14 \* (3.45)². Therefore, the area of this circle is approximately 38.47 square units.

 Q> What's the area difference between two circles with radii of 7 units and 10 units?
 I> 
 A> Let's calculate the area of both circles and find the Area(10) - Area(7). The area of a circle with a radius of 7 units is A1 = π(7)² ≈ 153.94 square units, and the area of a circle with a radius of 10 units is A2 = π(10)² ≈ 314.16 square units. So the area difference is 314.16 - 153.94 = approximately 160.22 square units, which is Area(10) - Area(7).


 84% 84/100 [08:09<01:38,  6.14s/it]INFO 2024-06-26 21:37:32,951 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Explain how to find the diameter from the area of a circle.
 I> 
 A> Deducing the diameter from the area of a circle requires the knowledge of the formula (A=πd²/4), where A represents the area and d is the diameter. By rearranging the formula to isolate 'd', you can calculate the diameter by solving for the square root of (4A/π).

 Q> What is the difference in the area between a circle with a radius of 4 cm and another one with a radius of 6 cm?
 I> 
 A> A circle with a radius of 6 cm has an area of π \* (6 cm)² = approximately 113.097 square cm. The area of the circle with a radius of 4 cm is π \* (4 cm)² = approximately 50.265 square cm. Consequently, the difference in the area between the two circles is approximately 62.832 square cm (113.097 - 50.265).


 86% 86/100 [08:19<01:21,  5.81s/it]INFO 2024-06-26 21:37:43,127 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> How would you determine the area of a circle with a 5-inch radius?
 I> 
 A> Using the formula A = πr², we must square the radius, 5 inches, then multiply by π. This results in A = π \* (5 inches)², leading to an area of approximately 78.54 square inches.

 Q> Consider a circle with an area of 154 square meters; what is its radius?
 I> 
 A> To find the radius from the area, you need to rearrange the formula to A = πr² so it becomes r = √(A/π). By substituting A with 154 square meters and taking the square root, you derive r ≈ 6.24 meters, meaning the radius is approximately 6.24 meters.


 88% 88/100 [08:29<01:06,  5.50s/it]INFO 2024-06-26 21:37:52,739 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 INFO 2024-06-26 21:37:55,104 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Imagine a circular water tank has a surface area of 452.39 square meters. How much would the area be if the water tank's radius is increased by 30%?
 I> **
 Existing area: 452.39 square meters, Increase in radius: 30%
 A> **
 First, find the original radius (r) using the formula A = πr², where A is the given area: √(452.39/π) meters. Next, calculate the increased radius (R) by adding 30% to the original radius: R = r + (0.3r). Finally, compute the increased area (A') using the formula A' = πR².

 Q> What is the area of a circle with a circumference of 22 centimeters (using π as 3.14)?
 I> **
 Circumference: 22 centimeters
 A> **
 To find the area of a circle with a given circumference (C), the formula is A = C²/(4π). Substitute 22 centimeters for C and 3.14 for π, then calculate the area A.


 90% 90/100 [08:41<00:57,  5.77s/it]INFO 2024-06-26 21:38:05,493 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Explain how to find the area of a circle using the radius value.
 I> Suppose a circle has a radius of 6 cm.
 A> To calculate the area of the circle, use the formula Area = π \* radius², where radius is the length from the center of the circle to any point on the circle's edge. In your case, the area is Area = π \* (6 cm)² ≈ 113.1 cm². This formula employs the constant pi (π), which is an irrational number approximately equal to 3.14159265. By squaring the radius value and multiplying by π, you find the area occupied by the circle.


 91% 91/100 [08:47<00:51,  5.73s/it]INFO 2024-06-26 21:38:11,031 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Develop a Python function to calculate the area of a circle, given its radius. By convention, π is represented as math.pi in Python.
 I> 
 A> Here is the requested Python function:

 def circle\_area(r):
 area = math.pi \* r ** 2
 return area

 You can try computing the area of a circle with a radius of 7 units like this: circle\_area(7)

 Q> Assume you have a circle with an area of 753.98 square meters. Approximate its diameter using π ≈ 3.14159.
 I> 
 A> First, let's rearrange the area formula to solve for the diameter. We get diameter = 2 \* √(A/π). Now, substitute 753.98 square meters for A and 3.14159 for π: diameter = 2 \* √(753.98 / 3.14159) ≈ 45.12 meters.


 93% 93/100 [08:57<00:38,  5.50s/it]INFO 2024-06-26 21:38:21,150 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Explain the formula used for calculating the area of a circle.
 I> 
 A> The formula employed for computing the area of a circle is A = πr², where A represents the area and r signifies the radius.

 Q> Incorporate this formula into a formula field in a database or spreadsheet for calculating the area of a circle given the radius.
 I> 
 A> To incorporate the formula for calculating the area of a circle in a formula field, you generally input:
 ```
 =[PI()]*[Radius]^2
 ```
 Adjust the field names according to your specific database or spreadsheet. The field containing the radius value should replace "Radius" and the field for the calculated area should replace "PI()".


 95% 95/100 [09:07<00:26,  5.25s/it]INFO 2024-06-26 21:38:30,619 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Suppose a circle has an area of 50 square inches. What is its radius?
 I> 
 A> To find the radius of a circle given its area, first use the formula A = πr² to isolate r. So, r = √(A/π). Given an area of 50 square inches, the radius would be √(50 sq in / π) ≈ 3.54 inches. Let me know if you need help with any other problems.

 Q> How does the area of a circle relate to that of a square inscribed in it?
 I> 
 A> The relationship between the area of a circle and that of a square inscribed in it is such that the square's area is always less than that of the circle. This is because the circle covers a larger space than the square. Specifically, the ratio of the areas is given by π/4 or approximately 0.7854.


 97% 97/100 [09:16<00:15,  5.15s/it]INFO 2024-06-26 21:38:40,512 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> What is the area of a circle with a radius of 6 feet? (Provide the exact answer using the mathematical value of π.)
 I> 
 A> The formula for the area of a circle is A = πr², so with a radius (r) of 6 feet, we can find the area by calculating π \* 6² = 3.14159 \* 36 = 113.10 cubic feet.

 Q> Explain how one calculates the area of a circle using the radius as a given element.
 I> 
 A> To determine the area of a circle with the given radius, square the radius value by multiplying it by itself: r \* r. Then, multiply that result by π, which is a mathematical constant that approximately equals 3.14159, to obtain the area in square units.


 99% 99/100 [09:26<00:05,  5.07s/it]INFO 2024-06-26 21:38:50,304 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->math->area
 Q> Explain the mathematical concept behind the formula used for determining the area of a circle.
 I> 
 A> The area of a circle is calculated using the formula A = πr², where A is the area and r is the radius. This formula results from inscribing the circle in a square with a side length equal to the circle’s diameter and then dividing the square into four congruent right triangles with their hypotenuses forming one-quarter of the circle’s circumference. The area of each triangle is derived by finding the product of its height and half its base, leading to A = 1/4 \* d², where d is the diameter. Finally, since A = πr² by definition, we divide the formula for the square’s area by 4 and solve for r² by substituting r = d/2.

 Q> What is the area of a circle with a radius of 5.5 meters? Provide your answer rounded to three decimal places. (Use the approximation of π as 3.14159.)
 I> 
 A> First, apply the area formula of A = πr² with π = 3.14159: A = 3.14159 \* (5.5)². The result when rounded to three decimal places is 98.171 square meters.


 101it [09:37,  5.21s/it]            
 101it [09:37,  5.72s/it]
 INFO 2024-06-26 21:39:01,313 generate_data.py:609: generate_data 101 instructions generated, 37 discarded due to format (see /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/STEM/math/area/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_29_23.log), 1 discarded due to rouge score
 INFO 2024-06-26 21:39:01,313 generate_data.py:613: generate_data Generation took 577.86s
 Completed 69.0 KiB/159.0 KiB (457.4 KiB/s) with 4 file(s) remaining
 upload: ../outputtopush/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T21_29_23.json to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/STEM/math/area/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T21_29_23.json
 Completed 69.0 KiB/159.0 KiB (457.4 KiB/s) with 3 file(s) remaining
 Completed 71.0 KiB/159.0 KiB (428.1 KiB/s) with 3 file(s) remaining
 upload: ../outputtopush/test_Mixtral-8x7B-Instruct-v0_2024-06-26T21_29_23.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/STEM/math/area/test_Mixtral-8x7B-Instruct-v0_2024-06-26T21_29_23.jsonl
 Completed 71.0 KiB/159.0 KiB (428.1 KiB/s) with 2 file(s) remaining
 Completed 137.3 KiB/159.0 KiB (561.9 KiB/s) with 2 file(s) remaining
 upload: ../outputtopush/train_Mixtral-8x7B-Instruct-v0_2024-06-26T21_29_23.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/STEM/math/area/train_Mixtral-8x7B-Instruct-v0_2024-06-26T21_29_23.jsonl
 Completed 137.3 KiB/159.0 KiB (561.9 KiB/s) with 1 file(s) remaining
 Completed 159.0 KiB/159.0 KiB (577.1 KiB/s) with 1 file(s) remaining
 upload: ../outputtopush/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_29_23.log to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/STEM/math/area/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_29_23.log
 compositional_skills/STEM/science/units_conversion/distance_conversion/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/STEM/science/units_conversion/distance_conversion/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/STEM/science/units_conversion/distance_conversion --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T21:39:03Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/STEM/science/units_conversion/distance_conversion/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 21:39:12,174 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> What is the distance from the Sun to Saturn in meters?
 I> 
 A> Hello! The average distance from the Sun to Saturn is about 1.43 x 10^12 meters. Let me know if you have any other questions or need assistance with something else.

 Q> How far is it from New York to Los Angeles in miles?
 I> 
 A> Hello! The distance from New York to Los Angeles is approximately 2,450 miles. Let me know if you have any other questions or need assistance with something else.


  2% 2/100 [00:09<07:23,  4.53s/it]INFO 2024-06-26 21:39:21,229 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Could you tell me, what is 7 kilometers in miles?
 I> 
 A> Hello! Sure, I can help you with that. To convert 7 kilometers into miles, you can use the conversion factor 1 kilometer ≈ 0.62 miles. Therefore, 7 kilometers is equivalent to approximately 4.35 miles. Let me know if you have any other questions or need assistance with something else.

 Q> Can you convert 1000 meters to miles?
 I> 
 A> Hello! To convert 1000 meters to miles, we need to use the conversion factors 1000 meters = 1 kilometer, and 1 kilometer ≈ 0.62 miles. Therefore, 1000 meters is equivalent to approximately 0.62 miles. Let me know if you have any other questions or need assistance with something else.


  4% 4/100 [00:18<07:37,  4.77s/it]INFO 2024-06-26 21:39:31,109 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Convert 500 centimeters to feet.
 I> 500 centimeters
 A> Hello! 500 centimeters is equal to 16.4 feet. Let me know if you have any other questions or need assistance with something else.

 Q> What is the equivalence of 1 kilometer to yards?
 I> 
 A> Hello! 1 kilometer is equivalent to approximately 1,093.61 yards. Let me know if you have any other questions or need assistance with something else.


  6% 6/100 [00:27<07:14,  4.62s/it]INFO 2024-06-26 21:39:40,012 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Please calculate the distance to the moon in miles using the given data: moon's average distance is 238,855 miles.
 I> 
 A> The distance to the moon is 238,855 miles.

 Q> Transform 12 feet to centimeters.
 I> 
 A> Hello! 12 feet is equivalent to approximately 365.76 centimeters. Let me know if you have any other questions or need assistance with something else.


  8% 8/100 [00:36<07:01,  4.59s/it]INFO 2024-06-26 21:39:49,070 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Convert the height of Mount Everest from meters to feet.
 I> 
 A> Hello! The height of Mount Everest is 8,848 meters. To convert this to feet, you can use the conversion factor 1 meter ≈ 3.28 feet. Therefore, Mount Everest is approximately 28,998 feet tall. Let me know if you have any other questions or need assistance with something else.

 Q> What is the distance between the Sun and Earth in kilometers?
 I> 
 A> Hello! The distance between the Sun and Earth varies throughout the year due to Earth's elliptical orbit. However, on average, the distance is about 150 million kilometers. Let me know if you have any other questions or need assistance with something else.


 10% 10/100 [00:46<07:01,  4.68s/it]INFO 2024-06-26 21:39:58,788 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Show me how many kilometers there are in 5 miles.
 I> 
 A> Hello! To convert 5 miles to kilometers, we need to use the conversion factor 1 mile ≈ 1.60934 kilometers. Therefore, 5 miles is equivalent to approximately 8.047 kilometers. Let me know if you have any other questions or need assistance with something else.

 Q> What is the equivalent of 1 light-year in parsecs?
 I> 
 A> Hello! A light-year is the distance that light travels in one year, which is about 9.461 x 10^12 kilometers. A parsec is a unit of length used in astronomy, equal to about 3.086 x 10^16 meters. To convert 1 light-year to parsecs, we can use the formula:

 light-years = distance / (1 light-year)

 Solving for distance in parsecs, we get:

 distance = light-years × (1 light-year)

 Therefore, 1 light-year is equivalent to approximately 0.306 parsecs. Let me know if you have any other questions or need assistance with something else.


 12% 12/100 [00:57<07:10,  4.89s/it]INFO 2024-06-26 21:40:09,379 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> How many light-years away is the closest star to the Sun, Proxima Centauri?
 I> 
 A> Hello! Proxima Centauri, the closest star to the Sun, is about 4.24 light-years away. A light-year is the distance that light travels in one year, which is approximately 9.46 trillion kilometers. Let me know if you have any other questions or need assistance with something else.

 Q> Translate 3216 feet to meters and give a real-world example of this distance.
 I> 
 A> Hello! To convert 3216 feet to meters, you can use the conversion factor 1 foot ≈ 0.3048 meters. Therefore, 3216 feet is equivalent to approximately 979.88 meters. In terms of real-world examples, this is roughly the height of the Eiffel Tower in Paris, France. Let me know if you have any other questions or need assistance with something else.


 14% 14/100 [01:07<07:04,  4.93s/it]INFO 2024-06-26 21:40:19,423 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Convert 500 feet to meters.
 I> 500 feet
 A> The equivalent of 500 feet in meters is approximately 152.4 meters. Let me know if you need help with other conversions or have any questions.

 Q> How far is the Moon from Earth in miles?
 I> 
 A> The average distance from the Earth to the Moon is about 238,855 miles. I can answer more questions or provide further assistance if needed.


 16% 16/100 [01:16<06:44,  4.81s/it]INFO 2024-06-26 21:40:28,507 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:40:30,064 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:40:31,630 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Convert 5 nautical miles to meters.
 I> 
 A> Hello! 5 nautical miles is equal to approximately 9,260 meters. If you have any other questions or need any more help, just let me know.

 Q> Could you explain how to convert light-years to parsecs?
 I> 
 A> Sure! To convert light-years to parsecs, simply divide the number of light-years by 3.262. For example, 1 light-year is equivalent to approximately 0.3066 parsecs. I'm here to help, so let me know if you have any other questions.


 18% 18/100 [01:28<07:11,  5.26s/it]INFO 2024-06-26 21:40:40,995 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> What is the equivalent of 1000 meters in miles?
 I> 
 A> Hello! To convert 1000 meters to miles, you can use the conversion factor 1 meter ≈ 0.000621 miles. Therefore, 1000 meters is equivalent to approximately 0.621 miles. Let me know if you have any other questions or need assistance with something else.

 Q> Could you translate 5 kilometers into nautical miles?
 I> 
 A> Hello! To convert 5 kilometers to nautical miles, you can use the conversion factor 1 kilometer ≈ 0.54 nautical miles. Therefore, 5 kilometers is equivalent to approximately 2.7 nautical miles. Let me know if you have any other questions or need assistance with something else.


 20% 20/100 [01:38<06:51,  5.14s/it]INFO 2024-06-26 21:40:50,778 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> What is the distance between the Earth and the Sun, expressed in astronomical units (AU)?
 I> 
 A> Hello! The average distance between the Earth and the Sun is 1 astronomical unit (AU). This is defined as the average distance between the Earth and the Sun, and is equal to approximately 93 million miles or 150 million kilometers. Let me know if you have any other questions or need assistance with something else.

 Q> Convert the distance between the Earth and the Moon from miles to kilometers.
 I> 
 A> Hello! The average distance between the Earth and the Moon is about 238,900 miles. To convert this distance to kilometers, you can use the conversion factor 1 mile ≈ 1.61 kilometers. Therefore, the average distance between the Earth and the Moon is about 384,400 kilometers. Let me know if you have any other questions or need assistance with something else.


 22% 22/100 [01:48<06:39,  5.12s/it]INFO 2024-06-26 21:41:00,882 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:41:02,444 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:41:05,102 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> What is the length of 25 kilometers in miles?
 I> 
 A> 25 kilometers is equal to about 15.5 miles. If you have any other conversions you'd like me to do, just let me know.

 Q> You are on a road trip and you have driven 100 miles. How many meters is this?
 I> 
 A> If you have driven 100 miles, that is equivalent to driving 160,934 meters. If you have any other distance conversions you need, just let me know!


 24% 24/100 [02:02<07:04,  5.59s/it]INFO 2024-06-26 21:41:14,230 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:41:15,828 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:41:18,758 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:41:20,854 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:41:24,129 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> What is the equivalent distance in feet of 200 meters?
 I> 
 A> Hello! To convert 200 meters to feet, you can use the conversion factor 1 meter ≈ 3.28 feet. Therefore, 200 meters is equivalent to approximately 656.17 feet. Let me know if you have any other questions or need assistance with something else.

 Q> Can you calculate the distance between the two cities, Paris and Rome, in kilometers?
 I> 
 A> Hello! The distance between Paris and Rome is approximately 1,243 kilometers. Let me know if you have any other questions or need assistance with something else.


 26% 26/100 [02:21<08:25,  6.83s/it]INFO 2024-06-26 21:41:33,619 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Kindly provide the conversion factor for yards to feet.
 I> 
 A> Hello! To convert yards to feet, you can use the conversion factor of 1 yard equals 3 feet. Therefore, 1 yard is equivalent to 3 feet. You can use this conversion factor to convert values from yards to feet. Let me know if you have any other questions or need assistance with something else.

 Q> Can you tell me how many meters there are in a furlong?
 I> 
 A> Hello! A furlong is a unit of length used in horse racing and is equal to 220 yards or approximately 201.17 meters. Therefore, there are about 201.17 meters in a furlong. Let me know if you have any other questions or need assistance with something else.


 28% 28/100 [02:31<07:30,  6.26s/it]INFO 2024-06-26 21:41:43,471 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:41:45,002 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Provide an example of converting 3.5 kilometers to yards.
 I> 
 A> Hello! To convert 3.5 kilometers to yards, we need to use the conversion factor 1 kilometer = 1,093.61 yards. Therefore, 3.5 kilometers is equivalent to approximately 3,812.16 yards. Let me know if you have any other questions or need assistance with something else.

 Q> Suppose you drove 200 miles a day for a week, how many kilometers is that?
 I> 
 A> Hello! To convert the distance from miles to kilometers, we need to use the conversion factor 1 mile ≈ 1.60934 kilometers. Therefore, if you drove 200 miles a day for a week (7 days), the total distance is approximately 2,239.54 kilometers. Let me know if you have any other questions or need assistance with something else.


 30% 30/100 [02:42<07:07,  6.11s/it]INFO 2024-06-26 21:41:55,028 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:41:56,668 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> How would you convert 3 nautical miles to meters?
 I> 
 A> Hello! 1 nautical mile is equivalent to 1,852 meters. Therefore, 3 nautical miles is equivalent to 5,556.5 meters. Let me know if you have any other questions or need assistance with something else.

 Q> What is the equivalent distance of 1 light-year in miles?
 I> 
 A> Hello! 1 light-year is equivalent to approximately 5,878,499,817,000 miles. Let me know if you have any other questions or need assistance with something else.


 32% 32/100 [02:53<06:43,  5.93s/it]INFO 2024-06-26 21:42:06,052 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:42:09,178 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:42:11,579 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Convert 4250 meters to feet.
 I> 
 A> Sure thing! 4250 meters is equal to approximately 13,943.5 feet. Let me know if there's anything else you need help with.

 Q> What's the equivalent of 0.61 miles in nautical miles?
 I> 
 A> 0.61 miles is equal to approximately 0.527 nautical miles. A nautical mile is a unit of length used for navigation at sea and is equal to about 1.852 kilometers. If you have any other conversions you'd like me to do, just let me know.


 34% 34/100 [03:08<07:03,  6.41s/it]INFO 2024-06-26 21:42:21,090 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Convert 3 kilometers to yards
 I> 
 A> Sure, I can help with that! One kilometer is equivalent to 1,093.61 yards. So, 3 kilometers would be about 3,280.83 yards.

 Q> What is the equivalent of 5 nautical miles in meters?
 I> 
 A> A nautical mile is equal to 1,852 meters. Therefore, 5 nautical miles would be equal to 9,260 meters.


 36% 36/100 [03:18<06:14,  5.85s/it]INFO 2024-06-26 21:42:30,190 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Given that the speed of light is roughly 299,792 kilometers per second, how many meters per second is that?
 I> 
 A> Hello! To convert the distance from kilometers per second to meters per second, we need to use the conversion factor 1 kilometer ≈ 1,000 meters. Therefore, the speed of light, which is approximately 299,792 kilometers per second, is equal to 299,792,000 meters per second. Let me know if you have any other questions or need assistance with something else.

 Q> What is the equivalent of 320 meters in yards?
 I> 
 A> Hello! To convert the distance from meters to yards, we need to use the conversion factor 1 meter ≈ 1.09361 yards. Therefore, 320 meters is equivalent to approximately 350.40 yards. Let me know if you have any other questions or need assistance with something else.


 38% 38/100 [03:28<05:48,  5.62s/it]INFO 2024-06-26 21:42:40,343 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:42:42,353 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:42:44,556 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Translate 100 kilometers into nautical miles.
 I> 
 A> To convert 100 kilometers to nautical miles, use the following formula:

 nautical\_miles = kilometers / 1.852

 Plug in the given value:

 nautical\_miles = 100 km / 1.852 km/nautical\_mile

 nautical\_miles = 54 nautical miles

 Thus, 100 kilometers is equal to 54 nautical miles. Let me know if you have other questions or need more assistance with this.

 Q> How many feet are there in 25 yards?
 I> 
 A> There are 75 feet in 25 yards because 1 yard is equal to 3 feet and we can simply multiply 3 by 25 to get 75 feet. Feel free to ask me any other math or conversion questions you might have.


 40% 40/100 [03:42<06:05,  6.10s/it]INFO 2024-06-26 21:42:54,758 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:42:57,273 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:42:59,205 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> How many feet are there in 12 meters?
 I> 
 A> Hello! To convert 12 meters to feet, you can use the conversion factor 1 meter is equal to 3.28084 feet. Therefore, 12 meters is equivalent to approximately 39.37 feet. Let me know if you have any other questions or need assistance with something else.

 Q> If a car travels at a speed of 60 miles per hour, how far will it go in 2.5 hours?
 I> 
 A> Hello! To find out how far a car travels at a speed of 60 miles per hour in 2.5 hours, you can use the formula distance = speed x time. Therefore, the car will travel 60 miles/hour x 2.5 hours = 150 miles. Let me know if you have any other questions or need assistance with something else.


 42% 42/100 [03:56<06:11,  6.40s/it]INFO 2024-06-26 21:43:09,003 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:43:11,851 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:43:14,388 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:43:16,759 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:43:18,692 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:43:20,079 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Please convert 2 miles to kilometers.
 I> 2 miles
 A> Hello! 2 miles is approximately 3.22 kilometers. Let me know if you have any other questions or need assistance with something else.

 Q> Convert 3 yards to centimeters.
 I> 3 yards
 A> Hello! 3 yards is equivalent to 274.32 centimeters. Let me know if you have any other questions or need assistance with something else.


 44% 44/100 [04:16<06:58,  7.48s/it]INFO 2024-06-26 21:43:28,991 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Convert 5 nautical miles to feet and present the result in scientific notation.
 I> 
 A> Hello! To convert 5 nautical miles to feet, we need to use the conversion factor 1 nautical mile = 6,076.11549 feet. Therefore, 5 nautical miles is equivalent to approximately 30,380,577.45 feet or 3.038057745 x 10^7 feet. Let me know if you have any other questions or need assistance with something else.

 Q> What is the difference between a league and a mile, and can you give an example of converting a league to miles?
 I> 
 A> Hello! A league is a unit of length used in navigation and is equal to 3 nautical miles or approximately 3.45 miles, while a mile is a unit of length used in the United States and other countries and is equal to 1,760 yards or approximately 1.61 kilometers. To convert 1 league to miles, we can use the conversion factor 1 league = 3 nautical miles = 3.45 miles. Therefore, 1 league is equivalent to approximately 3.45 miles. Let me know if you have any other questions or need assistance with something else.


 46% 46/100 [04:27<06:11,  6.87s/it]INFO 2024-06-26 21:43:39,902 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Please convert 5 miles to kilometers.
 I> 
 A> Hello! To convert miles to kilometers, you can use the conversion factor of 1 mile equals 1.60934 kilometers. Therefore, 5 miles is equivalent to approximately 8.0467 kilometers. Let me know if you have any other questions or need assistance with something else.

 Q> Can you give me the formula for converting inches to centimeters?
 I> 
 A> Hello! To convert inches to centimeters, you can use the formula: centimeters = inches x 2.54. For example, to convert 3 inches to centimeters, you would multiply 3 by 2.54 to get 7.62 centimeters. Let me know if you have any other questions or need assistance with something else.


 48% 48/100 [04:37<05:27,  6.29s/it]INFO 2024-06-26 21:43:49,762 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:43:51,574 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Could you please convert the distance from 100 miles to kilometers?
 I> 
 A> Of course! 100 miles is equivalent to approximately 160.934 kilometers. Let me know if you have any other questions or need assistance with something else.

 Q> What is the equivalent distance of 5000 meters in feet?
 I> 
 A> Hello! 5000 meters is equivalent to approximately 16,404 feet. Let me know if you have any other questions or need assistance with something else.


 50% 50/100 [04:48<05:02,  6.06s/it]INFO 2024-06-26 21:44:00,780 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:44:03,128 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> What is the equivalent of 100 meters in yards?
 I> 
 A> Hello! To convert 100 meters to yards, you can use the conversion factor 1 meter ≈ 1.09361 yards. Therefore, 100 meters is equivalent to approximately 109.361 yards. Let me know if you have any other questions or need assistance with something else.

 Q> Explain how to convert inches to centimeters using the unit conversion formula.
 I> 
 A> Hello! To convert inches to centimeters using the unit conversion formula, you can use the conversion factor 1 inch ≈ 2.54 centimeters. Here are the steps:
 1. Identify the number of inches you want to convert.
 2. Multiply that number by the conversion factor.
 For example, if you want to convert 5 inches to centimeters, you would do the following calculation: 5 inches x 2.54 centimeters/inch = 12.7 centimeters. Let me know if you have any other questions or need assistance with something else.


 52% 52/100 [05:01<04:55,  6.15s/it]INFO 2024-06-26 21:44:13,496 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> In what units of distance should you convert a distance of 200 meters?
 I> 
 A> When converting distances, it depends on what units you would like to convert 200 meters into. Common units of distance are:

 * Meters (m)
 * Centimeters (cm)
 * Decimeters (dm)
 * Kilometers (km)
 * Inches (in)
 * Feet (ft)
 * Nautical miles (nm)
 * Miles (mi)

 Let me know which specific units you would like me to convert the distance to.

 Q> Suppose you need to calculate the conversion of 4000 meters to miles; what is the resulting mileage?
 I> 
 A> To convert 4000 meters to miles, you can use the conversion factor 1 mile ≈ 1609.34 meters. So:

 miles = meters / 1609.34 meters/mile

 miles = 4000 meters / 1609.34 meters/mile

 miles ≈ 2.485 miles

 So, 4000 meters is equivalent to approximately 2.485 miles. Let me know if you have any other questions or need assistance with something else.


 54% 54/100 [05:11<04:31,  5.90s/it]INFO 2024-06-26 21:44:24,119 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:44:26,459 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Convert 10 feet to centimeters.
 I> 
 A> 1 foot is equal to 30.48 centimeters. To convert 10 feet to centimeters, multiply the number of feet by 30.48 centimeters per foot:

 centimeters = 10 feet \* 30.48 centimeters/foot

 centimeters = 304.8 centimeters

 Thus, 10 feet is equal to 304.8 centimeters.

 Q> How many yards are there in 15 meters?
 I> 
 A> To convert 15 meters to yards, let's use the conversion factor 1 yard ≈ 0.9144 meters. So:

 yards = 15 meters / 0.9144 meters/yard

 yards ≈ 16.39 yards

 Therefore, 15 meters is equivalent to approximately 16.39 yards.


 56% 56/100 [05:24<04:23,  5.99s/it]INFO 2024-06-26 21:44:36,566 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:44:38,534 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:44:40,106 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:44:43,483 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Please convert 12,000 meters to feet.
 I> 
 A> Sure thing! 12,000 meters is equal to 39,370 feet. Let me know if you need any other conversions.

 Q> How far is it from New York City to Los Angeles by air in nautical miles?
 I> 
 A> The approximate distance between New York City and Los Angeles by air is 2,450 nautical miles. This is equal to about 2,810 statute miles or 4,520 kilometers. Let me know if you have any other questions or conversions you'd like me to do.


 58% 58/100 [05:40<04:39,  6.65s/it]INFO 2024-06-26 21:44:52,933 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:44:55,040 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Without using a calculator, how can you estimate the conversion of 500 yards to meters?
 I> 
 A> Hello! Although I can't see your input, I will assume that you have asked for an estimation of 500 yards to meters without a calculator. A common estimation technique is to use the conversion factor of 1 yard ≈ 0.914 meters. Therefore, 500 yards would be about 500 x 0.914 = 457 meters. However, keep in mind that this is just an estimation and the exact value is 457.2 meters. Let me know if you have any other questions or need assistance with something else.

 Q> Name three common objects in everyday life that have a height of around 2 meters.
 I> 
 A> Hello! There are many common objects in everyday life that have a height of around 2 meters. Here are three examples:
 1. A standard refrigerator
 2. A dining table
 3. Most doors in homes or office buildings
 Let me know if you have any other questions or need assistance with something else.


 60% 60/100 [05:53<04:19,  6.50s/it]INFO 2024-06-26 21:45:05,219 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> How many light-seconds away is the moon from the Earth, given that it's about 0.0026 light-seconds away?
 I> 
 A> Sure! The moon is approximately 0.0026 light-seconds away from the Earth, which means it's roughly 384,400 kilometers (238,855 miles) away, considering the speed of light to be around 299,792 kilometers per second (186,282 miles per second). Let me know if you have any other questions or need help with something else.

 Q> What is the typical elevation difference between sea level and the top of Mount Everest?
 I> 
 A> Sea level commonly has an elevation of 0 meters, while the top of Mount Everest stands at about 8,848.86 meters (29,031.7 feet) above sea level, so the typical elevation difference between sea level and the peak of Mount Everest is approximately 8,848.86 meters (29,031.7 feet). Let me know if you have any other questions or need assistance with something else.


 62% 62/100 [06:03<03:53,  6.13s/it]INFO 2024-06-26 21:45:15,771 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:45:17,719 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:45:19,993 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> How many kilometers are there in 2000 yards?
 I> 
 A> There are 1.852 kilometers in 2000 yards, as 1 yard is equal to 0.9144 meters and 1 kilometer comprises 1000 meters.

 Q> Transform 10 furlongs into miles.
 I> 
 A> A furlong is equal to 1/8th of a mile; therefore, 10 furlongs would be equivalent to 1.25 miles.


 64% 64/100 [06:16<03:45,  6.27s/it]INFO 2024-06-26 21:45:28,987 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:45:31,288 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:45:33,479 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:45:35,374 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Please convert 500 meters to feet.
 I> 
 A> 1 meter is equivalent to 3.28084 feet. Therefore, 500 meters is equivalent to 1,640.42 feet. Let me know if you have any other questions or need assistance with something else.

 Q> What is the conversion factor for miles to kilometers?
 I> 
 A> Hello! 1 mile is equivalent to 1.60934 kilometers. Therefore, the conversion factor for miles to kilometers is 1.60934 kilometers per mile. Let me know if you have any other questions or need assistance with something else.


 66% 66/100 [06:32<03:49,  6.76s/it]INFO 2024-06-26 21:45:44,745 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Convert 100 feet to meters.
 I> 
 A> Sure, I'd be happy to help you with that! To convert feet to meters, you can use the conversion factor 1 foot ≈ 0.3048 meters. So, 100 feet is equivalent to approximately 30.48 meters. Let me know if you have any other questions or if there's anything else I can help you with!

 Q> Can you show me how to convert 5 miles to kilometers?
 I> 
 A> Of course! To convert miles to kilometers, you can use the conversion factor 1 mile ≈ 1.60934 kilometers. So, 5 miles is equivalent to approximately 8.04672 kilometers. Let me know if you have any other questions or if there's anything else I can help you with!


 68% 68/100 [06:42<03:17,  6.16s/it]INFO 2024-06-26 21:45:54,301 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Find out how many kilometers you can travel in one liter of gasoline at 50 kilometers per hour.
 I> 
 A> To find out how many kilometers you can travel in one liter of gasoline at 50 kilometers per hour, you can divide the speed by the fuel efficiency. For example, if your car has a fuel efficiency of 10 kilometers per liter, then you can travel:

 kilometers = 50 kilometers/hour ÷ 10 kilometers/liter

 kilometers = 5 liters

 Therefore, at 50 kilometers per hour, you can travel 5 kilometers on one liter of gasoline.

 Q> Express the height of the world's tallest building, the Burj Khalifa, in feet and meters.
 I> 
 A> The height of the Burj Khalifa is 828 meters, which is equivalent to approximately 2,722 feet. It is the tallest building in the world, with 163 floors and a total height that exceeds half a mile.


 70% 70/100 [06:52<02:55,  5.86s/it]INFO 2024-06-26 21:46:04,583 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Convert 5000 meters to feet and provide a real-world example.
 I> 
 A> Hello! To convert meters to feet, we need to use the conversion factor 1 meter ≈ 3.28084 feet. Therefore, 5000 meters is equivalent to approximately 16,404.2 feet.

 In a real-world example, 5000 meters is the same as running approximately 3.1 miles (which is 5000 meters times 0.000621371, or the number of feet in a mile). Let me know if you have any other questions or need assistance with something else.

 Q> What is the distance from the Earth to the Moon in miles?
 I> 
 A> Hello! The distance from the Earth to the Moon varies depending on the position of the Moon in its orbit, ranging from about 225,623 miles to 252,088 miles (or about 363,104 kilometers to 405,696 kilometers). On average, the Earth-Moon distance is about 238,855 miles (or about 384,400 kilometers). Let me know if you have any other questions or need assistance with something else.


 72% 72/100 [07:02<02:39,  5.69s/it]INFO 2024-06-26 21:46:15,162 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> What is the height of Mount Everest in meters?
 I> 
 A> Mount Everest, located in the Himalayas, is the highest mountain peak in the world, with an elevation of 8,848.86 meters above sea level, as per the latest measurement by China and Nepal in 2020.

 Q> How many kilometers long is the Great Barrier Reef?
 I> 
 A> The Great Barrier Reef is a remarkable natural structure located off the coast of Queensland, Australia. It is the largest coral reef system globally, stretching approximately 2,300 kilometers in length. This stunning ecosystem is home to an incredibly diverse range of marine life and is a popular destination for tourists from around the world.


 74% 74/100 [07:12<02:20,  5.39s/it]INFO 2024-06-26 21:46:24,569 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Convert 100 kilometers into miles.
 I> 
 A> Certainly! One kilometer is approximately equal to 0.621371 miles. Therefore, 100 kilometers is equal to 62.1371 miles. This is a significant distance, making it perfect for a long road trip or a challenging bike ride.

 Q> What is the distance between New York City and Los Angeles in miles?
 I> 
 A> New York City and Los Angeles are two iconic cities located on opposite coasts of the United States. The distance between these two cities is approximately 2,448 miles (3,939 kilometers) by road. Whether you're traveling by car, train, or plane, this journey requires a substantial amount of time and planning.


 76% 76/100 [07:21<02:05,  5.21s/it]INFO 2024-06-26 21:46:34,143 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Please convert a speed of 60 miles per hour to meters per second.
 I> 1 hour = 3600 seconds
 1 mile = 1609.34 meters
 A> To convert miles per hour to meters per second, we can use the conversion factors you provided. Specifically, we have 1 mile = 1609.34 meters and 1 hour = 3600 seconds. Therefore, a speed of 60 miles per hour is equal to 26.822 meters per second (i.e., 60 miles/hour \* (1609.34 meters/mile) / (3600 seconds/hour) = 26.822 meters/second).

 Q> Can you help me understand the difference between a kilometer and a mile?
 I> 
 A> Certainly! A kilometer (km) and a mile are units of length used in different systems of measurement. Specifically, a kilometer is a unit of the International System of Units (SI), which is largely used in scientific and technical contexts, while a mile is a unit of the U.S. customary system, which is used mainly in the United States.

 One kilometer is equal to 1000 meters, which is the base unit of length in the SI system. On the other hand, one mile is equal to 5280 feet, or about 1609.34 meters, as you correctly pointed out. Therefore, 1 mile is slightly longer than 1 kilometer (namely, 1 mile ≈ 1.60934 kilometers).

 I hope this helps! Let me know if you have any other questions or need assistance with something else.


 78% 78/100 [07:33<01:58,  5.39s/it]INFO 2024-06-26 21:46:45,734 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:46:47,677 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:46:50,323 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:46:52,923 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Convert the length of a marathon (26.2 miles) to kilometers.
 I> 
 A> 26.2 miles is equivalent to 42.16 kilometers. Is there anything else you need help with?

 Q> How many feet are there in 500 meters?
 I> 
 A> 500 meters is equal to 1,640.42 feet. Let me know if you have any other distance conversions!


 80% 80/100 [07:49<02:03,  6.17s/it]INFO 2024-06-26 21:47:01,712 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:47:03,340 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Calculate the distance in furlongs between New York, NY and Los Angeles, CA, approximately 2,450 miles apart.
 I> 
 A> In order to calculate the distance between New York, NY and Los Angeles, CA in furlongs, first, convert the total distance of 2,450 miles. Considering 1 mile is equal to 8 furlongs, multiply the total miles by the conversion factor. So, 2,450 miles times 8 furlongs/mile gives you an approximate distance of 19,600 furlongs.

 Q> If a rover moves 100 yards on Mars, how much space does it cover on Earth, assuming the atmospheric pressure of both planets can be disregarded?
 I> 
 A> On Earth, a rover moving 100 yards would cover an area slightly different than on Mars because the gravity and atmospheric conditions are different. However, if we only consider the linear distance, 100 yards would be equal to 91.44 meters or 100.58 yards on Earth, since 1 yard is the same on both planets.


 82% 82/100 [08:01<01:50,  6.12s/it]INFO 2024-06-26 21:47:13,733 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:47:15,785 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:47:17,048 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:47:19,273 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> If you have a distance of 500 meters, how many feet is it?
 I> 
 A> Hello! Sure, I can help you with that. To convert 500 meters into feet, you can use the conversion factor 1 meter ≈ 3.28 feet. Therefore, 500 meters is equivalent to approximately 1640.42 feet. Let me know if you have any other questions or need assistance with something else.

 Q> Name five countries with a land area of over 2 million square kilometers.
 I> 
 A> Hello! There are many countries in the world that have a land area of over 2 million square kilometers. Here are five examples:
 1. Canada
 2. China
 3. Russia
 4. United States
 5. Brazil
 Let me know if you have any other questions or need assistance with something else.


 84% 84/100 [08:16<01:44,  6.56s/it]INFO 2024-06-26 21:47:28,890 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:47:31,238 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Convert the distance from the Moon to the Earth (around 238,900 miles) to kilometers.
 I> 
 A> The distance from the Moon to the Earth is approximately 238,900 miles. To convert this distance to kilometers, we can use the conversion factor of 1 mile to 1.60934 kilometers. Therefore, the distance in kilometers is 384,402 kilometers. That's quite a long distance, isn't it?

 Q> If an airplane cruises at an altitude of approximately 35,000 feet, how can you convert this distance to miles?
 I> 
 A> Sure thing! If an airplane cruises at an altitude of 35,000 feet, we can convert this distance to miles using the conversion factor of 1 foot to 0.000189394 miles. Therefore, the altitude in miles is 6.524 miles. That's a little over 33,000 feet!


 86% 86/100 [08:29<01:30,  6.46s/it]INFO 2024-06-26 21:47:41,323 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:47:43,132 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Can you explain how to convert inches to millimeters?
 I> 
 A> Sure! To convert inches to millimeters, you can use the conversion factor 1 inch is equal to 25.4 millimeters. This means that you can multiply the number of inches by 25.4 to get the number of millimeters. For example, if you have 5 inches, you can multiply 5 by 25.4 to get 127 millimeters. Let me know if you have any other questions or if you need further clarification.

 Q> What is the distance in nautical miles of 12 kilometers?
 I> 
 A> Hello! 12 kilometers is equivalent to approximately 6.51 nautical miles. Let me know if you have any other questions or need assistance with something else.


 88% 88/100 [08:40<01:14,  6.24s/it]INFO 2024-06-26 21:47:52,774 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:47:54,321 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Transform 350 feet to yards.
 I> 
 A> 350 feet is equal to 116.67 yards. If you have any other conversions to do, just let me know.

 Q> What is the distance in meters between two points that are 500 feet apart?
 I> 
 A> 500 feet is equal to approximately 152.4 meters. So if two points are 500 feet apart, they are about 152.4 meters apart. I hope that helps!


 90% 90/100 [08:51<00:59,  5.95s/it]INFO 2024-06-26 21:48:03,305 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Suppose you're converting nautical miles to statute miles. How far is one nautical mile in regular miles?
 I> 
 A> Hello! A nautical mile is slightly longer than a regular mile, with 1 nautical mile equating to about 1.1508 statute miles. I hope this helps! Do you have any other questions or tasks you would like me to help with?

 Q> What is the length in meters of the Empire State Building, which is approximately 1,454 feet tall?
 I> 
 A> Hi there! The Empire State Building, with a height of approximately 1,454 feet, is around 443 meters tall, given that 1 foot is equal to 0.3048 meters. If you have any other questions, feel free to ask!


 92% 92/100 [09:00<00:44,  5.61s/it]INFO 2024-06-26 21:48:12,936 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 INFO 2024-06-26 21:48:15,416 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Could you please express 1000 light-years in astronomical units?
 I> 
 A> An astronomical unit (AU) is equivalent to 149,597,870.7 kilometers or 0.000004848136811 light-years. Therefore, 1000 light-years equal approximately 206,264,806 astronomical units.

 Q> How long is the Great Barrier Reef in meters?
 I> 
 A> The Great Barrier Reef, located in Australia, is the largest coral reef system globally, stretching for approximately 2,300 kilometers (or 2,300,000 meters).


 94% 94/100 [09:12<00:34,  5.73s/it]INFO 2024-06-26 21:48:24,952 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Could you explain how to convert kilometers to miles?
 I> 
 A> Certainly! To convert kilometers to miles, you can use the following formula: miles = kilometers / 1.60934. This is because there are approximately 1.60934 kilometers in one mile. Let me know if you have any other questions or conversions you'd like me to do.

 Q> What is the distance to the moon in meters?
 I> 
 A> The average distance from the Earth to the Moon is about 385,000 kilometers, or approximately 385,000,000 meters. This distance can vary depending on the positions of the Earth and the Moon in their orbits. Let me know if you have any other questions or need assistance with something else.


 96% 96/100 [09:22<00:21,  5.45s/it]INFO 2024-06-26 21:48:34,591 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> Please provide the measurement of 5000 yards in miles.
 I> 
 A> Sure! To convert yards to miles, you can use the conversion factor 1 yard ≈ 0.000568 miles. Therefore, 5000 yards is equivalent to approximately 2.8 miles. I hope this helps!

 Q> In what unit is the distance from the moon to Earth's surface commonly measured?
 I> 
 A> The distance from the moon to Earth's surface is commonly measured in miles or kilometers.


 98% 98/100 [09:31<00:10,  5.18s/it]INFO 2024-06-26 21:48:43,661 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->STEM->science->units_conversion->distance_conversion
 Q> kindly calculate the equivalent length in kilometers of 250 miles for me.
 I> 
 A> Certainly! 250 miles is equivalent to approximately 402.34 kilometers.

 Q> How many nautical miles are there in 600 statute (land) miles?
 I> 
 A> There are approximately 520 nautical miles in 600 statute (land) miles.


 100% 100/100 [09:40<00:00,  4.97s/it]
 100% 100/100 [09:40<00:00,  5.80s/it]
 INFO 2024-06-26 21:48:52,620 generate_data.py:609: generate_data 100 instructions generated, 88 discarded due to format (see /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/STEM/science/units_conversion/distance_conversion/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_39_12.log), 0 discarded due to rouge score
 INFO 2024-06-26 21:48:52,620 generate_data.py:613: generate_data Generation took 580.52s
 Completed 37.6 KiB/153.1 KiB (263.1 KiB/s) with 4 file(s) remaining
 upload: ../outputtopush/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_39_12.log to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/STEM/science/units_conversion/distance_conversion/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_39_12.log
 Completed 37.6 KiB/153.1 KiB (263.1 KiB/s) with 3 file(s) remaining
 Completed 96.5 KiB/153.1 KiB (531.5 KiB/s) with 3 file(s) remaining
 upload: ../outputtopush/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T21_39_12.json to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/STEM/science/units_conversion/distance_conversion/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T21_39_12.json
 Completed 96.5 KiB/153.1 KiB (531.5 KiB/s) with 2 file(s) remaining
 Completed 98.1 KiB/153.1 KiB (415.8 KiB/s) with 2 file(s) remaining
 upload: ../outputtopush/test_Mixtral-8x7B-Instruct-v0_2024-06-26T21_39_12.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/STEM/science/units_conversion/distance_conversion/test_Mixtral-8x7B-Instruct-v0_2024-06-26T21_39_12.jsonl
 Completed 98.1 KiB/153.1 KiB (415.8 KiB/s) with 1 file(s) remaining
 Completed 153.1 KiB/153.1 KiB (604.4 KiB/s) with 1 file(s) remaining
 upload: ../outputtopush/train_Mixtral-8x7B-Instruct-v0_2024-06-26T21_39_12.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/STEM/science/units_conversion/distance_conversion/train_Mixtral-8x7B-Instruct-v0_2024-06-26T21_39_12.jsonl
 compositional_skills/extraction/services_agreement/reasoning/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/extraction/services_agreement/reasoning/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/services_agreement/reasoning --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T21:48:55Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/extraction/services_agreement/reasoning/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 21:49:03,408 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What are the required coverage limits for General Liability Insurance as per the provided services agreement?
 I> 
 A> The required coverage limits for General Liability Insurance as per the provided services agreement are not less than $350,000 on account of any one person and $990,000 for each occurrence of property damage and personal injury.

 Q> What is the consequence of failing to obtain insurance coverage as per the services agreement’s requirements?
 I> 
 A> Failing to obtain insurance coverage without the County's written approval would constitute a material breach of the Agreement and would automatically terminate the Agreement as per the services agreement.


  2% 2/100 [00:09<07:26,  4.56s/it]INFO 2024-06-26 21:49:12,531 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:49:15,132 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:49:23,595 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What should I do if I violate the terms of the agreement and the county decides to terminate the contract?
 I> 4. Termination. Consultant may terminate this Agreement at any time by giving the County written notice of not less than sixty (60) days. County may terminate this Agreement at any time in the event that Consultant violates the terms of this Agreement or fails to produce a result that meets the specifications of this Agreement. In the event of termination, payments will be made to Consultant for all work performed up to the date of termination.
 <>
 A> You should provide written notice of thirty (30) days if you intend to terminate the contract due to your violation of the terms. If the county decides to terminate the contract, ensure all work specified in the agreement is completed before the effective date of termination.

 Q> Are there any restrictions on the sub-consultants I can hire for this project?
 I> 
 A> Yes, Section 8 states that you shall require any of your agents or sub-consultants who enter upon the county's premises to maintain like insurance as mandated by the services agreement and provide certificates of such insurance, agents and sub-consultants, upon request. It also states that such insurance shall be primary insurance to the full limits of the liability and not cancelled without thirty (30) days prior written notice to the County.


  4% 4/100 [00:30<13:16,  8.29s/it]INFO 2024-06-26 21:49:34,339 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:49:39,254 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:49:43,726 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Explain the necessary procedures for a subcontractor to follow to demonstrate their insurance compliance with the services agreement.
 I> 
 A> A subcontractor can demonstrate their insurance compliance with the services agreement by obtaining and providing the county with certificates of insurance for the types and amounts specified in the agreement. The subcontractor must maintain Comprehensive General Liability Insurance with limits of not less than $990,000 for each occurrence of property damage and personal injury, and maintain like insurance if entering upon the county's premises. The subcontractor shall also ensure their insurance is primary insurance to the full limits of liability, and not cancelled without 30 days prior written notice to the county.

 Q> Has the services agreement authorized the county to automatically terminate the agreement if the consultant fails to provide written notice of the reduction or cancellation of automobile liability insurance?
 I> 8. Automobile Liability insurance in those instances where Consultant uses an automobile, regardless of ownership, for the performance of the Services. Consultant shall carry insurance, written on the comprehensive automobile form insuring all owned and nonowned automobiles with limits of not less than $100,000 (bodily injury per person), $300,000 (each accident) and $50,000 (property damage). Insurance coverage shall not be reduced below the limits described above or cancelled without County's written approval of such reduction or cancellation.
 A> Yes, the services agreement has authorized the county to automatically terminate the agreement if the consultant fails to provide written notice of the reduction or cancellation of automobile liability insurance. Such a breach of the agreement would relieve the county of any further obligations under the agreement, and the county may pursue any remedies available under law for the consultant's breach.


  6% 6/100 [00:52<14:38,  9.34s/it]INFO 2024-06-26 21:49:55,520 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What is the financial liability of the sub-consultant as per services agreement in case of damage to the county's property or injury to the county's employees on the job site?
 I> 
 A> As per the services agreement, the sub-consultant is required to provide Comprehensive General Liability Insurance with limits of not less than $350,000 on account of any one person and $990,000 for each occurrence of property damage and personal injury. This insurance must be primary insurance to the full limits of liability and not cancelled without thirty (30) days prior written notice to the County. Therefore, the sub-consultant is financially liable for damages to the County's property or injuries to the County's employees on the job site up to the specified limits in the insurance policy.

 Q> As a sub-consultant, what kind of insurance do I need to obtain and maintain under the services agreement during the contract term?
 I> 
 A> As a sub-consultant, you are required to obtain and maintain Comprehensive General Liability Insurance, Standard Workers' Compensation Insurance, and Automobile Liability Insurance during the contract term as per the services agreement. The Comprehensive General Liability Insurance must have limits of not less than $350,000 for each person and $990,000 for each occurrence of property damage and personal injury. The Standard Workers' Compensation Insurance must comply with the law of Colorado. The Automobile Liability Insurance must have limits of not less than $100,000 (bodily injury per person), $300,000 (each accident), and $50,000 (property damage) and insure all owned and nonowned automobiles used for the performance of the Services.


  8% 8/100 [01:03<12:15,  8.00s/it]INFO 2024-06-26 21:50:07,392 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What are the time limits for the County to make payments to the Consultant for invoices submitted in accordance with this Agreement?
 I> 
 A> The time limit for the County to make payments to the Consultant for invoices submitted in accordance with this Agreement is within twenty-five (25) days of the receipt thereof.

 Q> What is the primary insurance requirement for the Consultant in the event of a claim for property damage?
 I> 8. Indemnification and Insurance. Consultant shall indemnify and hold harmless the County from and against all claims, damages, losses, and expenses arising out of or resulting from acts or omissions of the Consultant, Consultant's sub-Consultants or otherwise arising out of the performance of services by Consultant. No later than seven days after execution of this Agreement, Consultant shall provide the County with certificates of insurance evidencing the types and amounts of insurance specified below:

 A. Standard Workers' Compensation as required by law in the State of Colorado; and

 B. Comprehensive General Liability Insurance for operations and contractual liability adequate to cover the liability assumed hereunder with limits of not less than $350,000 on account of any one person and $990,000 for each occurrence of property damage and personal injury; and

 C. Automobile Liability insurance in those instances where Consultant uses an automobile, regardless of ownership, for the performance of the Services. Consultant shall carry insurance, written on the comprehensive automobile form insuring all owned and nonowned automobiles with limits of not less than $100,000 (bodily injury per person), $300,000 (each accident) and $50,000 (property damage).

 Insurance coverage shall not be reduced below the limits described above or cancelled without County's written approval of such reduction or cancellation. Reduction, cancellation or termination of insurance coverage, or failure to obtain insurance coverage, without the County's written approval shall constitute a material breach of the Agreement and shall automatically terminate the Agreement. Consultant shall require that any of its agents or sub-consultants who enter upon the County's premises shall maintain like insurance. Certificates of such insurance, of agents and sub-consultants, shall be provided to the County upon request. With regard to all insurance, such insurance shall:

 A. Be primary insurance to the full limits of liability herein before stated and, should County have other valid insurance, County insurance shall be excess insurance only; and

 B. Not cancelled without thirty (30) days prior written notice to the County.
 A> The primary insurance requirement for the Consultant in the event of a claim for property damage is Comprehensive General Liability Insurance with a limit of $990,000 per occurrence, as specified in section 8 B.


 10% 10/100 [01:18<11:29,  7.66s/it]INFO 2024-06-26 21:50:21,500 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What are the specific requirements for the insurance coverage's notice of cancellation, termination, or material change in the services agreement?
 I> 
 A> As per the services agreement, any notice of cancellation, termination, or material change in the insurance coverage must be provided to the other party in writing at least ten (10) working days before such notice takes effect. The notice must state the date when the cancellation, termination, or material change will become effective.

 Q> Who is responsible for obtaining insurance coverage under the services agreement?
 I> 
 A> Under the services agreement, the sub-consultant is responsible for obtaining and maintaining insurance coverage, including Comprehensive General Liability Insurance, Standard Workers' Compensation Insurance, and Automobile Liability Insurance, during the contract term.


 12% 12/100 [01:27<09:48,  6.68s/it]INFO 2024-06-26 21:50:31,088 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:50:36,887 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What is the required minimum limit for the comprehensive general liability insurance as stated in the services agreement?
 I> 
 A> The required minimum limit for the comprehensive general liability insurance is $350,000 on account of any one person and $990,000 for each occurrence of property damage and personal injury.

 Q> What happens if the consultant cancels the insurance coverage without the county's written approval?
 I> 8. Indemnification and Insurance. Consultant shall indemnify and hold harmless the County from and against all claims, damages, losses, and expenses arising out of or resulting from acts or omissions of the Consultant, Consultant's sub-Consultants or otherwise arising out of the performance of services by Consultant. No later than seven days after execution of this Agreement, Consultant shall provide the County with certificates of insurance evidencing the types and amounts of insurance specified below:

 A. Standard Workers' Compensation as required by law in the State of Colorado; and

 B. Comprehensive General Liability Insurance for operations and contractual liability adequate to cover the liability assumed hereunder with limits of not less than $350,000 on account of any one person and $990,000 for each occurrence of property damage and personal injury; and

 C. Automobile Liability insurance in those instances where Consultant uses an automobile, regardless of ownership, for the performance of the Services. Consultant shall carry insurance, written on the comprehensive automobile form insuring all owned and nonowned automobiles with limits of not less than $100,000 (bodily injury per person), $300,000 (each accident) and $50,000 (property damage).

 Insurance coverage shall not be reduced below the limits described above or cancelled without County's written approval of such reduction or cancellation. Reduction, cancellation or termination of insurance coverage, or failure to obtain insurance coverage, without the County's written approval shall constitute a material breach of the Agreement and shall automatically terminate the Agreement. Consultant shall require that any of its agents or sub-consultants who enter upon the County's premises shall maintain like insurance. Certificates of such insurance, of agents and sub-consultants, shall be provided to the County upon request. With regard to all insurance, such insurance shall:

 A. Be primary insurance to the full limits of liability herein before stated and, should County have other valid insurance, County insurance shall be excess insurance only; and B. Not cancelled without thirty (30) days prior written notice to the County.
 A> Cancelling the insurance coverage without the county's written approval shall constitute a material breach of the Agreement and shall automatically terminate the Agreement.


 14% 14/100 [01:47<11:05,  7.74s/it]INFO 2024-06-26 21:50:50,933 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:50:53,774 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Explain what the consequence is if the sub-consultant fails to obtain insurance coverage without County's written approval under the services agreement.
 I> 
 A> If the sub-consultant fails to obtain insurance coverage without County's written approval, it constitutes a material breach of the agreement, and the county has the right to automatically terminate the agreement.

 Q> Looking at section 2.4, what is the minimum amount of insurance coverage that the sub-consultant is required to have under the services agreement?
 I> 2.4 Insurance. The sub-consultant shall at all times during the term of this agreement maintain insurance coverage against all risks and liabilities ordinarily insured against by contractors engaged in similar business and performing similar services in the same locality and having the same or similar experience and capabilities as the sub-consultant. Such insurance coverage shall provide complete coverage for all operations of the sub-consultant, including but not limited to operations performed at the Countys facilities. The sub-consultant shall obtain minimum coverage for general liability insurance of not less than $1,000,000 per occurrence, comprehensive automobile insurance for owned, non-owned and hired autos of not less than $1,000,000 per accident, and standard workers compensation insurance of not less than $500,000 per employee.
 A> Under section 2.4, the sub-consultant is required to obtain a minimum coverage for general liability insurance of not less than $1,000,000 per occurrence, comprehensive automobile insurance for owned, non-owned and hired autos of not less than $1,000,000 per accident, and standard workers compensation insurance of not less than $500,000 per employee.


 16% 16/100 [02:02<10:38,  7.60s/it]INFO 2024-06-26 21:51:05,543 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:51:10,111 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> According to the services agreement, what are the deliverables expected from the sub-consultant?
 I> 
 A> The services agreement requires the sub-consultant to deliver the following:

 1. Provide and maintain adequate staffing resources so that the work will be completed in a timely and competent manner.
 2. Design and prepare the scope of work and approach for the project described in the agreement.
 3. Submit all necessary permit applications, approvals, and documentation on behalf of the Consultant.
 4. Provide Construction Phase Services, including conducting progress meetings, investigating claims, and providing necessary documentation to the Consultant.
 5. Provide Professional Liability Insurance coverage and maintain Workers' Compensation Insurance as required.

 Q> What is the duration of the agreement term according to sub-clause 3 of the services agreement?
 I> 
 A> Sub-clause 3. Term of the Agreement outlines that the contract term begins on _______ and ends on _______.


 18% 18/100 [02:16<10:17,  7.53s/it]INFO 2024-06-26 21:51:20,249 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:51:22,275 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:51:25,838 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:51:27,812 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Explain the indemnification clause found in the services agreement.
 I> 
 A> The indemnification clause in this services agreement requires the sub-consultant to compensate the consultant for any losses, damages, claims, or expenses arising from the sub-consultant or their subcontractors' negligent actions or breach of this agreement. This clause protects the consultant from risks associated with the sub-consultant's work.

 Q> Describe the circumstances in which termination of the agreement may occur.
 I> 
 A> According to the services agreement, either party can terminate it by providing a written termination notice. Termination is allowed if the other party breaches the agreement, including delays of substantial work or failure to pay fees. The agreement may also be terminated if either party becomes insolvent.


 20% 20/100 [02:33<10:27,  7.85s/it]INFO 2024-06-26 21:51:37,377 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What consequences would the breach of confidentiality cause, as mentioned in the agreement?
 I> 
 A> The breach of confidentiality, as stated in Section 6.2 of the agreement, would cause significant harm, including the revelation of proprietary information and trade secrets, leading to potential financial and reputational damage for both parties.

 Q> Identify the warranties provided by the contractor in the agreement.
 I> 
 A> The contractor has provided several warranties in the agreement, including the warranty of work quality in Section 2.1, the warranty on materials used in Section 2.2, and the warranty on fitness for purpose in Section 2.3. Each warranty establishes the contractor's commitment to delivering a quality service to the client.


 22% 22/100 [02:43<08:57,  6.89s/it]INFO 2024-06-26 21:51:47,018 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:51:49,141 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What is the procedure for providing the certificate of insurance under the services agreement?
 I> 
 A> As per the services agreement, the sub-consultant must provide the certificate of insurance to the contractor at least 10 days before the contract starts and annually thereafter. The certificate should be provided to the contractor's risk management department and must include the policy numbers, effective dates, and the insurance carrier's name.

 Q> What is the consequence of not maintaining the required insurance coverage as per the services agreement?
 I> 
 A> Failure to maintain the required insurance coverage as per the services agreement may result in the termination of the contract and the sub-consultant's liability for any damages or losses arising from such failure.


 24% 24/100 [02:55<08:22,  6.61s/it]INFO 2024-06-26 21:51:58,784 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Explain the responsibilities of the sub-consultant regarding the protection of confidential information as stated in the services agreement.
 I> 
 A> As per the services agreement, the sub-consultant is responsible for protecting confidential information by using reasonable care to prevent unauthorized disclosure, use, or access. This includes limiting access to confidential information to only those who need to know and securing physical and electronic records containing confidential information.

 Q> What are the specified circumstances under which either party may terminate the services agreement?
 I> 
 A> Either party may terminate the services agreement if the other party breaches any material term or condition of this Agreement, fails to perform their obligations under this Agreement, or becomes insolvent or bankrupt.


 26% 26/100 [03:04<07:26,  6.04s/it]INFO 2024-06-26 21:52:08,197 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Identify the termination clause in the services agreement between the County and Consultant.
 I> 
 A> The termination clause in the services agreement between the County and Consultant is as follows: "Either party may terminate this Agreement upon giving the other party thirty (30) days written notice of such termination."

 Q> What are the responsibilities of the Consultant in regards to environmental protection during the construction project, as per the services agreement?
 I> 
 A> As per the services agreement, the Consultant is required to comply with all applicable federal, state, and local laws, regulations, and ordinances including, but not limited to, those relating to the protection and preservation of the environment during the construction project. The Consultant shall also comply with all best management practices for environmental protection that are customary in the County.


 28% 28/100 [03:14<06:46,  5.64s/it]INFO 2024-06-26 21:52:17,680 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What are the payment terms of the services agreement?
 I> The term of this agreement is from January 1, 2022 to December 31, 2022. Payments will be made in installments of $10,000 on the first day of each month, starting on February 1, 2022, and ending on January 1, 2023.
 A> Payments are to be made in installments of $10,000 on the first day of each month, starting on February 1, 2022 and ending on January 1, 2023.

 Q> What are the consequences of termination of the services agreement by the Consultant?
 I> Consultant may terminate this Agreement at any time by giving the County written notice of not less than sixty (60) days.
 A> If the Consultant terminates the agreement, they will need to provide 60 days written notice to the County.


 30% 30/100 [03:24<06:21,  5.45s/it]INFO 2024-06-26 21:52:27,667 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Explain the scope of the work as per the agreement for the service provider.
 I> 
 A> The work scope for the service provider is spelled out in Section 4 and covers consulting, designing, and installing required systems and equipment to meet the County's needs. This includes system configuration and testing, staff training, and documentation, among other tasks.

 Q> How does the agreement specify indemnification for the service provider?
 I> 
 A> The agreement states under Section 11 that the service provider will indemnify and hold the County, its officers, employees, and agents harmless against any and all claims, losses, damages, liabilities, costs, and expenses (including reasonable attorneys' fees) arising out of any breach of the service provider's warranties or obligations under the agreement.


 32% 32/100 [03:33<05:56,  5.25s/it]INFO 2024-06-26 21:52:37,222 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:52:38,800 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:52:41,123 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:52:43,023 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Identify the consequences for the sub-consultant in case of non-compliance with the payment terms outlined in the services agreement.
 I> 
 A> Failure to comply with the payment terms as outlined in the services agreement may result in the sub-consultant being subject to late fees, suspension of services, or termination of the agreement.

 Q> What is the specified notice period for the termination of the services agreement?
 I> 6. Termination. This Agreement may be terminated by either Party upon providing thirty (30) days written notice to the other Party.
 A> The specified notice period for the termination of the services agreement is thirty (30) days, as specified in section 6.


 34% 34/100 [03:49<06:33,  5.96s/it]INFO 2024-06-26 21:52:52,493 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> In the provided services agreement, summarize the scope of work for the Consultant.
 I> **
 <noinput>
 A> **
 The scope of work for the Consultant in the services agreement includes providing all necessary labor, materials, and services to complete the designated services, including designing, construction, and development.


 35% 35/100 [03:54<06:21,  5.87s/it]INFO 2024-06-26 21:52:57,918 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Identify any provisions in the services agreement that outline the procedures for dispute resolution.
 I> 
 A> The services agreement includes a provision that mandates dispute resolution through mediation and, if necessary, arbitration. Either party may initiate mediation by providing written notice to the other party, and the mediator's decision will be final and binding on both parties.

 Q> What are the consequences of failing to comply with the payment terms stated in the services agreement?
 I> <nointerest>
 A> Failure to comply with the payment terms in the services agreement may result in late fees, suspension or termination of services, or damage to the party's credit and reputation.


 37% 37/100 [04:03<05:43,  5.45s/it]INFO 2024-06-26 21:53:07,171 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Could you clarify the payment schedule specified in section 5.2 of the services agreement?
 I> Section 5.2 of the services agreement states that "Payments shall be made within 30 days of the receipt of the invoice."
 A> According to the services agreement, following the receipt of each invoice, the payment should be made within a 30-day period.

 Q> Who is responsible for covering the legal fees concerning any dispute arising under the services agreement?
 I> 
 A> The services agreement states that each party is responsible for its own legal fees and expenses concerning any disputes arising under the agreement, unless otherwise provided.


 39% 39/100 [04:13<05:17,  5.20s/it]INFO 2024-06-26 21:53:16,504 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What are the insurance coverage requirements for the consultant who uses an automobile for the performance of services?
 I> 8. Indemnification and Insurance. Consultant shall indemnify and hold harmless the County from and against all claims, damages, losses, and expenses arising out of or resulting from acts or omissions of the Consultant, Consultant's sub-Consultants or otherwise arising out of the performance of services by Consultant. No later than seven days after execution of this Agreement, Consultant shall provide the County with certificates of insurance evidencing the types and amounts of insurance specified below:

 A. Standard Workers' Compensation as required by law in the State of Colorado; and

 B. Comprehensive General Liability Insurance for operations and contractual liability adequate to cover the liability assumed hereunder with limits of not less than $350,000 on account of any one person and $990,000 for each occurrence of property damage and personal injury; and

 C. Automobile Liability insurance in those instances where Consultant uses an automobile, regardless of ownership, for the performance of the Services. Consultant shall carry insurance, written on the comprehensive automobile form insuring all owned and nonowned automobiles with limits of not less than $100,000 (bodily injury per person), $300,000 (each accident) and $50,000 (property damage).

 Insurance coverage shall not be reduced below the limits described above or cancelled without County's written approval of such reduction or cancellation. Reduction, cancellation or termination of insurance coverage, or failure to obtain insurance coverage, without the County's written approval shall constitute a material breach of the Agreement and shall automatically terminate the Agreement. Consultant shall require that any of its agents or sub-consultants who enter upon the County's premises shall maintain like insurance. Certificates of such insurance, of agents and sub-consultants, shall be provided to the County upon request. With regard to all insurance, such insurance shall:

 A. Be primary insurance to the full limits of liability herein before stated and, should County have other valid insurance, County insurance shall be excess insurance only; and B. Not cancelled without thirty (30) days prior written notice to the County.
 A> The consultant who uses an automobile for the performance of services shall carry Automobile Liability insurance with limits of not less than $100,000 (bodily injury per person), $300,000 (each accident) and $50,000 (property damage). This insurance must cover all owned and nonowned automobiles used for the performance of services.

 Q> How many days of prior written notice is required for cancelling any insurance coverage?
 I> 
 A> Thirty (30) days prior written notice is required for cancelling any insurance coverage per the terms of the services agreement.


 41% 41/100 [04:27<05:41,  5.79s/it]INFO 2024-06-26 21:53:30,658 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Provide a concise explanation of the dispute resolution process according to the terms of the services agreement.
 I> 
 A> The dispute resolution process according to the services agreement involves engaging in negotiations to resolve any disputes, and if the dispute remains unresolved, either party may initiate mediation or arbitration as specified in Section 13.


 42% 42/100 [04:32<05:33,  5.74s/it]INFO 2024-06-26 21:53:36,189 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Can the County terminate the services agreement before the completion of the construction project? If so, what conditions must be met?
 I> 
 A> Yes, the services agreement can be terminated before the completion of the construction project if either party breaches any of its material obligations and fails to cure such breach within thirty (30) days after receiving written notice from the non-breaching party.

 Q> Which party bears the risk of loss of or damage to the construction project during the construction period, as specified in the services agreement?
 I> 
 A> As per the services agreement, the Consultant bears the risk of loss of or damage to the construction project during the construction period, except in cases where the loss or damage was caused by the County's negligence or wrongful act.


 44% 44/100 [04:42<05:02,  5.39s/it]INFO 2024-06-26 21:53:45,652 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:53:47,885 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> identify the limitations on the Consultant's liability in the services agreement.
 I> **
 <noinput>
 A> **
 The Consultant's liability is limited to the amount paid to the Consultant for the services under the services agreement. The Consultant is not liable for any consequential damages or any other indirect damages.

 Q> What is the compensation structure for the Consultant outlined in the services agreement?
 I> **
 <noinput>
 A> **
 The compensation structure for the Consultant outlined in the services agreement includes a fixed fee of $50,000, plus reimbursable expenses for the services rendered.


 46% 46/100 [04:53<04:57,  5.50s/it]INFO 2024-06-26 21:53:57,090 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:54:01,757 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What are the consequences for breaching the non-disclosure clause in the agreement?
 I> 
 A> Any breach of the non-disclosure clause will result in the immediate termination of the agreement, and the offending party will be required to pay liquidated damages equal to fifty thousand dollars ($50,000) per incident.

 Q> Explain the terms of payment outline in the agreement.
 I> 
 A> Payment terms require that the client pay an initial deposit of ten thousand dollars ($10,000) upon signing the agreement. The client will then be invoiced monthly for the services rendered and must pay the invoice within thirty (30) days of receipt.


 48% 48/100 [05:07<05:10,  5.97s/it]INFO 2024-06-26 21:54:11,043 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Explain the implications of dispute resolution mechanisms in the services agreement.
 I> Under Dispute Resolution, the agreement states, "Any disputes arising out of this Services Agreement will be resolved by arbitration in accordance with the Commercial Arbitration Rules of the American Arbitration Association."
 A> The dispute resolution mechanism mentioned implies that any disagreements arising from the services agreement should be handled through arbitration under the Commercial Arbitration Rules of the American Arbitration Association. This means disputes will not be resolved in court but through a neutral, third-party arbitrator. The decision reached in the arbitration will be final, binding, and enforceable on either party. This mechanism helps maintain privacy, save time, and reduce costs compared to litigation.

 Q> What is the specific requirement placed upon the Consultant related to staffing in sub-clause 4.1 of the agreement?
 I> 
 A> Sub-clause 4.1 of the agreement specifies that the Consultant is obligated to do the following regarding staffing:
 Ensure that key personnel assigned to the project have the appropriate skills, training, and experience and will maintain such qualifications during the term of the agreement.


 50% 50/100 [05:17<04:45,  5.70s/it]INFO 2024-06-26 21:54:21,252 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:54:23,814 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:54:28,639 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:54:30,822 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What is the maximum liability for damages assumed by the Contractor under the terms of the contract?
 I> 
 A> Under the terms of the contract, the Contractor's maximum liability for damages is limited to $100,000 as specified in sub-clause 6.3(a).

 Q> Identify the termination clause that can be invoked by either party involved in the agreement.
 I> 
 A> Clause 11.4(b) is the termination clause that can be invoked by either party involved in the agreement. It states that either party may terminate the agreement with immediate effect if the other party commits a material breach of the agreement.


 52% 52/100 [05:36<05:27,  6.83s/it]INFO 2024-06-26 21:54:39,951 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:54:44,037 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:54:47,029 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What are the fee and payment terms mentioned in the services agreement?
 I> 5. Payment. (a) Fees. The County shall pay Consultant a fee of $10,000 for the services rendered. The fee will be payable in four (4) installments. The first installment shall be due upon execution of this Agreement, the second installment upon the submission of a draft report, the third installment upon submission of a final report, and the fourth installment upon Acceptance of the final report.
 A> The fees for the services mentioned in the agreement are $10,000, which will be paid in four installments after the execution of the Agreement, upon submission of each draft report, final report, and Acceptance of the final report.

 Q> Upon which conditions could the county terminate the contract and how should the Consultant proceed accordingly?
 I> 
 A> The county can terminate the contract if the Consultant violates the terms of the agreement or fails to produce a result that meets the specifications. If termination occurs, the Consultant should ensure all the work specified in the agreement is completed and receive payments for all work performed up to the date of termination.


 54% 54/100 [05:54<05:41,  7.42s/it]INFO 2024-06-26 21:54:57,475 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Explain the termination clause outlined in the services agreement.
 I> 
 A> The services agreement can be terminated by either party with or without cause, upon giving 30 days' written notice or upon the payment of an agreed-upon termination fee. In the case of termination due to a breach of the agreement, the non-breaching party will be entitled to recover all damages incurred as a result of the breach.

 Q> What are the responsibilities of the Consultant regarding confidential information under the services agreement?
 I> 
 A> The Consultant must maintain the confidentiality of all confidential information received from the Client and must not disclose such information to any third party without the prior written consent of the Client. This confidentiality obligation will continue even after the termination of the services agreement.


 56% 56/100 [06:03<04:51,  6.61s/it]INFO 2024-06-26 21:55:07,014 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:55:09,783 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:55:11,558 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Explain the indemnification provision in the services agreement between the Company and Service Provider.
 I> 
 A> The indemnification provision in the services agreement between the Company and Service Provider states that the Service Provider agrees to defend, indemnify, and hold the Company harmless from any liability, claims, or damages arising out of the Service Provider's negligence or willful misconduct in providing the services.

 Q> What is the duration of the services agreement between Acme Inc. and the Consultant?
 I> 
 A> The duration of the services agreement between Acme Inc. and the Consultant is one year, starting from the effective date stated in the agreement and ending one year later.


 58% 58/100 [06:17<04:42,  6.72s/it]INFO 2024-06-26 21:55:20,916 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What is the designated office for submitting the certificate of insurance within the County department?
 I> 
 A> The certificate of insurance should be submitted to the Risk Management Department of the County.

 Q> Can you summarize the conditions and requirements for the termination of the services agreement by the County?
 I> 
 A> The services agreement can be terminated by the County if the consultant breaches the agreement by reducing, cancelling or terminating the insurance coverage without the County's written approval. The agreement will also be terminated if the consultant fails to obtain insurance coverage without the County's written approval.


 60% 60/100 [06:26<04:02,  6.07s/it]INFO 2024-06-26 21:55:30,043 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:55:31,765 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What is the compensation structure stipulated for the Contractor as per clause 6.3 in the agreement?
 I> 
 A> Clause 6.3 of the agreement states that the Contractor shall be compensated according to a fixed fee schedule, inclusive of any applicable taxes, expenses, costs, or deductions. This fee schedule shall be agreed upon by both parties beforehand and outlined in the agreement.

 Q> Please highlight and explain the provisions made for dispute resolution under the contract in clause 8.
 I> 
 A> Clause 8 of the contract details the Dispute Resolution process. It outlines a structured procedure where the parties must first engage in good faith negotiations to resolve any disputes arising between them. If these discussions prove unsuccessful, the dispute will then progress to mediation or binding arbitration. The decision of the arbitrator is final and binding on the parties involved.


 62% 62/100 [06:38<03:46,  5.95s/it]INFO 2024-06-26 21:55:41,435 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:55:44,167 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Clarify the liability clause in the services agreement.
 I> 7. Liability. Neither Party shall be liable to the other for any indirect, incidental, special, or consequential damages, arising out of or in connection with the performance or breach of this Agreement.
 A> The liability clause states that neither party is liable for indirect, incidental, special, or consequential damages, even if the other party breaches the agreement.

 Q> Who is responsible for the confidentiality under the services agreement?
 I> 5. Confidentiality. Each Party agrees to keep confidential all non-public information received from the other Party during the term of this Agreement, whether orally, visually, or in writing.
 A> Both parties are responsible for maintaining the confidentiality of non-public information received from the other party during the term of the agreement.


 64% 64/100 [06:50<03:36,  6.01s/it]INFO 2024-06-26 21:55:53,745 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Is there a confidentiality clause present in the provided legal contract? If yes, quote it.
 I> 
 A> Yes, there is a confidentiality clause present in the legal contract. It states, "Each party agrees to preserve and protect the confidentiality of all Confidential Information."


 65% 65/100 [06:55<03:26,  5.91s/it]INFO 2024-06-26 21:55:59,186 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What does the termination clause in the contract suggest regarding the circumstances under which the agreement can be ended by the service provider?
 I> 11. Termination. This Agreement shall continue in effect until June 30, 2022, unless terminated earlier in accordance with the provisions of this paragraph.

 A. Either party may terminate this Agreement on 30 days' written notice to the other if this Agreement is being materially breached by the other party and such breach is not cured within 14 days of receipt of written notice thereof.

 B. If either party files a petition in bankruptcy, becomes insolvent, makes an assignment for the benefit of creditors, or if a receiver is appointed for the party or for the party's property, the other party shall have the right to terminate this Agreement upon giving written notice to the affected party to that effect.

 C. The County may terminate this Agreement at any time for any reason upon 30 days' written notice to the Consultant.
 A> The termination clause indicates that either party can terminate the agreement if it is being materially breached by the other party and such breach is not cured within 14 days of receipt of written notice. Additionally, either party can terminate the agreement if the other party files a petition in bankruptcy, becomes insolvent, makes an assignment for the benefit of creditors, or if a receiver is appointed for the party or for the party's property. The County can also terminate the agreement at any time for any reason upon 30 days' written notice to the Consultant.

 Q> Which section of the provided legal contract describes the provisions for payment to the service provider?
 I> 
 A> Section 6 of the legal contract describes the provisions for payment to the service provider.


 67% 67/100 [07:07<03:15,  5.91s/it]INFO 2024-06-26 21:56:10,991 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Given the services agreement, what types of insurance coverage must the consultant maintain, at a minimum?
 I> 8. Insurance. Consultant shall maintain at its own expense during the delivery of the Services the following insurance with minimum limits as follows:

 A. comprehensive general liability Insurance (CGL) in the amount of Four million dollars ($4,000,000) per occurrence and Four million dollars ($4,000,000) in the aggregate;

 B. commercial automobile liability insurance in the amount of Four million dollars ($4,000,000) per occurrence and Five million dollars ($5,000,000) in the aggregate, including contractual liability; and

 C. workers' compensation coverage as required by law.
 A> As per the services agreement, the consultant must maintain the following types of insurance coverage at a minimum: 
 1. Comprehensive General Liability Insurance (CGL) in the amount of $4,000,000 per occurrence and $4,000,000 in the aggregate.
 2. Commercial Automobile Liability Insurance in the amount of $4,000,000 per occurrence and $5,000,000 in the aggregate, including contractual liability.
 3. Workers' compensation coverage as required by law.

 Q> What actions would constitute a material breach of the services agreement that would allow the county to terminate the agreement?
 I> 
 A> As per the services agreement, the following actions would constitute a material breach of the agreement that would allow the county to terminate it:
 1. Reduction, cancellation, or termination of insurance coverage, or failure to obtain insurance coverage, without the County's written approval
 2. Failure to maintain the specified insurance coverage
 3. Failure to comply with any other terms or conditions of the agreement.


 69% 69/100 [07:19<03:04,  5.96s/it]INFO 2024-06-26 21:56:23,097 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Indicate the key obligations and responsibilities of the service provider in the agreement.
 I> 
 A> The service provider is obligated to provide quality and timely services as specified in the agreement's Section 4. They are responsible for consultancy, design, installation, and testing of the required systems and equipment. They need to train the county personnel, provide documentation, and provide ongoing support.

 Q> What are the terms for the payment of the service provider?
 I> 3. Payment. The County agrees to pay the Service Provider: (a) a consulting fee of $200 per hour, and (b) actual, reasonable, and necessary expenses incurred by the Service Provider during the performance of this Agreement,
 A> The terms for the payment of the service provider include a consulting fee of $200 per hour (as mentioned in Section 3 (a)), and actual, reasonable, and necessary expenses incurred by the Service Provider during their work (as stated in Section 3 (b)).


 71% 71/100 [07:29<02:43,  5.64s/it]INFO 2024-06-26 21:56:32,998 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:56:35,273 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What are the responsibilities of the Contractor, according to the provided agreement?
 I> The Contractor is responsible for managing and delivering the marketing and communication campaign for the World Music Festival.
 A> As outlined in the agreement, the Contractor's responsibilities include managing the marketing and communication campaign, creating promotional materials, and coordinating with stakeholders, as stated in Section 2.1.

 Q> Explain the dispute resolution mechanism under the software license agreement.
 I> 
 A> Based on the software license agreement, any disputes arising between the parties will be settled through a binding arbitration conducted by a neutral third-party, as outlined in Section 9.4, instead of litigation in court.


 73% 73/100 [07:41<02:33,  5.70s/it]INFO 2024-06-26 21:56:44,659 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> In the provided contract, point out the duration of the service agreement and any renewal terms.
 I> 
 A> The service agreement lasts for an initial period of three (3) years, as outlined in Section 1.1. After this period, the agreement will automatically renew for successive one (1) year terms unless a party provides written notice of termination at least ninety (90) days prior to the expiration date.

 Q> How does the dispute resolution process work according to the agreement?
 I> 
 A> According to Section 12, any disputes arising from or relating to this agreement will first be attempted to be resolved amicably through friendly negotiations between the parties. In case the dispute remains unresolved, it will be submitted to binding arbitration in accordance with the Commercial Arbitration Rules maintained by the American Arbitration Association (AAA).


 75% 75/100 [07:50<02:15,  5.43s/it]INFO 2024-06-26 21:56:54,323 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What is the duration of the agreement and the conditions for its renewal, as specified in the contract?
 I> 8. Term. This Agreement shall become effective on the Effective Date and shall continue in effect for a period of one (1) year commencing on the Effective Date, unless terminated earlier in accordance with the provisions of this paragraph. Thereafter, the Agreement will automatically renew for successive one-year terms unless either party provides written notice of non-renewal at least thirty (30) days before the end of the then-current term.
 A> The agreement becomes effective on the Effective Date and continues for a period of one (1) year, with automatic renewals for successive one-year terms unless there's written notice of non-renewal at least thirty (30) days before the end of the then-current term.

 Q> Determine the extent of the confidentiality obligations imposed on the service provider in relation to the client’s proprietary information.
 I> 5. Confidential Information. The Consultant acknowledges that during the course of its services under this Agreement it may be furnished with or have access to Confidential Information of the County. The Consultant agrees to preserve and protect the confidentiality of all Confidential Information of the County and to use it only for the purpose of providing the services under this Agreement.
 A> The service provider is expected to preserve and protect the confidentiality of all confidential information of the client, utilizing it solely for the purpose of delivering services under the agreement.


 77% 77/100 [08:01<02:04,  5.42s/it]INFO 2024-06-26 21:57:05,094 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Identify any limitations on liability of the Service Provider in the agreement.
 I> The Service Provider's liability is limited to a maximum amount of $100,000 for any direct damages arising from the services provided under this agreement.
 A> The agreement limits the Service Provider's liability to a maximum amount of $100,000 for any direct damages arising from the services provided as per Section 5.3.

 Q> What termination clause is included in the provided services agreement?
 I> Either party may terminate this agreement with a 30-day written notice.
 A> The services agreement includes a termination clause allowing either party to terminate the agreement with a 30-day written notice as stated in Section 8.2.


 79% 79/100 [08:11<01:49,  5.22s/it]INFO 2024-06-26 21:57:14,631 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What is the disputes resolution mechanism in the agreement?
 I> 
 A> Disputes or claims that cannot be resolved amicably between the parties will be resolved through binding arbitration, unless forum selection or venue is otherwise specified in the agreement.


 80% 80/100 [08:21<02:01,  6.08s/it]INFO 2024-06-26 21:57:24,698 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Who is responsible for obtaining any necessary permits as outlined in the contract?
 I> 
 A> According to the contract, the responsibility for obtaining any necessary permits falls on the Contractor, as stated in section 4.2.

 Q> What type of damages is the liability of the Contractor capped at in the agreement?
 I> The liability of the Contractor in the event of personal injury, property damage, or any other damages is capped at a maximum amount of $500,000 as outlined in the agreement.
 A> The liability of the Contractor is capped at a maximum amount of $500,000 for personal injury, property damage, and any other damages.


 82% 82/100 [08:30<01:40,  5.58s/it]INFO 2024-06-26 21:57:33,899 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Highlight the dispute resolution mechanism mentioned in the contract.
 I> 
 A> The dispute resolution mechanism mentioned in the contract involves mediation as the primary means of resolving conflicts, followed by arbitration if mediation fails. Mediation and arbitration proceedings will be conducted in accordance with the rules of the American Arbitration Association (AAA).

 Q> How are the services and deliverables defined in the contract?
 I> 
 A> In the contract, the services and deliverables are defined as the provision of technical expertise, software development, and related consulting services, with specified milestones and deadlines for deliverables such as the completion of software modules, system integration, and documentation.


 84% 84/100 [08:39<01:24,  5.25s/it]INFO 2024-06-26 21:57:43,029 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What is the time period for the County to approve or reject the Consultant's invoices, as stated in the services agreement?
 I> The County shall approve or reject any Consultant's invoice not later than fifteen (15) days after receipt of the invoice.
 A> The County has 15 days from receiving a Consultant's invoice to approve or reject it.

 Q> What is the compensation rate for additional services requested by the County, as indicated in the services agreement?
 I> The compensation rate for additional services requested by the County is at the Consultant's standard rate for such services.
 A> The compensation rate for additional services requested by the County is the Consultant's standard rate.


 86% 86/100 [08:48<01:10,  5.06s/it]INFO 2024-06-26 21:57:52,350 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Explain the change order process outlined in the services agreement.
 I> 
 A> The services agreement outlines a change order process involving a written request from either party requesting changes to the scope of work, a meeting to discuss the impact of the changes, and a written change order signed by both parties.

 Q> What is the procedure for handling disputes outlined in the services agreement?
 I> 
 A> The services agreement establishes a dispute resolution process involving negotiation between the parties, followed by mediation, and finally arbitration if the dispute remains unresolved.


 88% 88/100 [08:57<00:58,  4.88s/it]INFO 2024-06-26 21:58:01,279 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What are the consequences of failing to obtain insurance coverage as specified in the agreement?
 I> 8. Indemnification and Insurance. Insurance coverage shall not be reduced below the limits described above or cancelled without County's written approval of such reduction or cancellation. Reduction, cancellation or termination of insurance coverage, or failure to obtain insurance coverage, without the County's written approval shall constitute a material breach of the Agreement and shall automatically terminate the Agreement.
 A> Failing to obtain insurance coverage as specified in the agreement is considered a material breach of the agreement and will result in automatic termination of the agreement.


 89% 89/100 [09:04<00:57,  5.25s/it]INFO 2024-06-26 21:58:08,185 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:58:10,869 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:58:12,962 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Explain the obligations of the client regarding dispute resolution, as per article 8 of the agreement.
 I> 8.1 Any dispute, controversy, or claim arising out of or in connection with this Agreement, including any disputes regarding the breach, termination, or validity thereof, shall be referred to and finally resolved by binding arbitration, administered by the American Arbitration Association in accordance with its Commercial Arbitration Rules. The place of the arbitration shall be [city, state]. The number of arbitrators shall be one (1). The language to be used in the arbitration proceedings shall be English.
 A> According to article 8, any dispute, controversy, or claim arising out of or in connection with the agreement must be referred to and finally resolved by binding arbitration administered by the American Arbitration Association under its Commercial Arbitration Rules. The arbitration will take place in [city, state], and will be conducted in English. There will be one arbitrator. This arbitration provision applies to disputes regarding the breach, termination, or validity of the agreement.


 90% 90/100 [09:15<01:04,  6.45s/it]INFO 2024-06-26 21:58:19,239 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:58:21,962 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What is the governing law for this agreement?
 I> This agreement shall be governed by and construed in accordance with the laws of the State of California.
 A> The governing law for this agreement is the law of the State of California.

 Q> Identify the parties responsible for the obligations under the services agreement.
 I> XYZ Inc. as the client and ABC Corporation as the service provider have entered into this agreement for the provision of software development services by ABC Corporation to XYZ Inc.
 A> XYZ Inc. is the client, and ABC Corporation is the service provider responsible for providing software development services under the services agreement.


 92% 92/100 [09:27<00:50,  6.28s/it]INFO 2024-06-26 21:58:31,227 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What are the limits of automobile liability insurance coverage that the Consultant is required to maintain?
 I> 8. Indemnification and Insurance. Consultant shall indemnify and hold harmless the County from and against all claims, damages, losses, and expenses arising out of or resulting from acts or omissions of the Consultant, Consultant's sub-Consultants or otherwise arising out of the performance of services by Consultant. No later than seven days after execution of this Agreement, Consultant shall provide the County with certificates of insurance evidencing the types and amounts of insurance specified below:

 A. Standard Workers' Compensation as required by law in the State of Colorado; and

 B. Comprehensive General Liability Insurance for operations and contractual liability adequate to cover the liability assumed hereunder with limits of not less than $350,000 on account of any one person and $990,000 for each occurrence of property damage and personal injury; and

 C. Automobile Liability insurance in those instances where Consultant uses an automobile, regardless of ownership, for the performance of the Services. Consultant shall carry insurance, written on the comprehensive automobile form insuring all owned and nonowned automobiles with limits of not less than $100,000 (bodily injury per person), $300,000 (each accident) and $50,000 (property damage).
 A> The Consultant is required to maintain Automobile Liability insurance with limits of not less than $100,000 (bodily injury per person), $300,000 (each accident), and $50,000 (property damage), as specified in section 8 C.

 Q> What are the consequences of reducing, cancelling, or terminating insurance coverage without the County's written approval?
 I> 8. Indemnification and Insurance. Consultant shall indemnify and hold harmless the County from and against all claims, damages, losses, and expenses arising out of or resulting from acts or omissions of the Consultant, Consultant's sub-Consultants or otherwise arising out of the performance of services by Consultant. No later than seven days after execution of this Agreement, Consultant shall provide the County with certificates of insurance evidencing the types and amounts of insurance specified below:

 A. Standard Workers' Compensation as required by law in the State of Colorado; and

 B. Comprehensive General Liability Insurance for operations and contractual liability adequate to cover the liability assumed hereunder with limits of not less than $350,000 on account of any one person and $990,000 for each occurrence of property damage and personal injury; and

 C. Automobile Liability insurance in those instances where Consultant uses an automobile, regardless of ownership, for the performance of the Services. Consultant shall carry insurance, written on the comprehensive automobile form insuring all owned and nonowned automobiles with limits of not less than $100,000 (bodily injury per person), $300,000 (each accident) and $50,000 (property damage).

 Insurance coverage shall not be reduced below the limits described above or cancelled without County's written approval of such reduction or cancellation. Reduction, cancellation or termination of insurance coverage, or failure to obtain insurance coverage, without the County's written approval shall constitute a material breach of the Agreement and shall automatically terminate the Agreement. Consultant shall require that any of its agents or sub-consultants who enter upon the County's premises shall maintain like insurance. Certificates of such insurance, of agents and sub-consultants, shall be provided to the County upon request. With regard to all insurance, such insurance shall:

 A. Be primary insurance to the full limits of liability herein before stated and, should County have other valid insurance, County insurance shall be excess insurance only; and

 B. Not cancelled without thirty (30) days prior written notice to the County.
 A> Reducing, cancelling, or terminating insurance coverage without the County's written approval shall constitute a material breach of the Agreement, leading to the automatic termination of the Agreement, as specified in section 8.


 94% 94/100 [09:45<00:42,  7.09s/it]INFO 2024-06-26 21:58:48,450 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:58:51,185 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Identify the obligations and responsibilities of the parties involved in the contract.
 I> 1. Obligations of the County. The County agrees to provide Consultant with all necessary data and documentation to enable Consultant to carry out the Services.
 2. Obligations of Consultant. Consultant shall maintain the confidentiality of all data and documentation provided by the County, and shall not disclose such information to any third party.
 A> The County's obligations in the contract include providing necessary data and documentation, while Consultant's obligations include maintaining the confidentiality of the provided information and not disclosing it to any third party.


 95% 95/100 [09:52<00:36,  7.26s/it]INFO 2024-06-26 21:58:56,416 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> What are the consequences of a breach of contract for the service provider under this agreement?
 I> 3. Breach. If the Service Provider breaches this Agreement, the Client shall have the right, in addition to any other remedies available at law or in equity, to recover monetary damages from the Service Provider in an amount equal to the actual damages suffered by the Client as a result of such breach, or at the Client's option, to terminate this Agreement in accordance with the provisions hereof.
 A> According to the breach clause, if the Service Provider breaches the agreement, the Client has the right to recover monetary damages or terminate the agreement.

 Q> Under what conditions can the client recover damages or terminate the agreement due to a breach of contract by the service provider?
 I> 
 A> Based on the agreement, if the Service Provider breaches the contract, the Client can recover monetary damages or terminate the agreement. The Client has the option to pursue either remedy, but they must do so in accordance with the provisions of the agreement.


 97% 97/100 [10:03<00:19,  6.47s/it]INFO 2024-06-26 21:59:06,563 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 INFO 2024-06-26 21:59:08,572 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> Identify and describe the responsibilities of the consultant during the project.
 I> 
 A> The consultant is responsible for completing the tasks required to deliver the project, providing access to required documentation, and engaging in project meetings. The consultant is also responsible for communicating with the County and maintaining insurance coverage.

 Q> What is the timeline given for the completion of the work outlined in the services agreement?
 I> 
 A> The services agreement requires the consultant to complete the work within 120 days from the effective date of the agreement, subject to extensions granted for uncontrollable circumstances.


 99% 99/100 [10:14<00:06,  6.15s/it]INFO 2024-06-26 21:59:17,614 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->reasoning
 Q> In the given legal contract, detail the conditions under which either party can terminate the agreement prematurely.
 I> **
 4. Termination. Either Party may terminate this Agreement upon thirty (30) days prior written notice if the other Party (a) is in material breach of any of its obligations under this Agreement and fails to cure such breach within thirty (30) days after receipt of written notice from the non-breaching Party; or (b) files a petition in bankruptcy or is adjudicated bankrupt or insolvent or makes an assignment for the benefit of creditors or has a receiver or trustee appointed for a substantial portion of its property.
 A> **
 Either party can terminate this agreement with thirty days of written notice, if the other party fails to correct a material breach within thirty days of receiving the written notice. Additionally, there is a provision for termination if the other party files for bankruptcy, is adjudicated bankrupt or insolvent, assigns for creditors' benefit, or has a receiver or trustee appointed for its substantial property.


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 INFO 2024-06-26 21:59:25,782 generate_data.py:609: generate_data 100 instructions generated, 63 discarded due to format (see /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/services_agreement/reasoning/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_49_03.log), 1 discarded due to rouge score
 INFO 2024-06-26 21:59:25,782 generate_data.py:613: generate_data Generation took 622.47s
 Completed 19.5 KiB/231.7 KiB (113.1 KiB/s) with 4 file(s) remaining
 upload: ../outputtopush/test_Mixtral-8x7B-Instruct-v0_2024-06-26T21_49_03.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/services_agreement/reasoning/test_Mixtral-8x7B-Instruct-v0_2024-06-26T21_49_03.jsonl
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 upload: ../outputtopush/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_49_03.log to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/services_agreement/reasoning/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_49_03.log
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 upload: ../outputtopush/train_Mixtral-8x7B-Instruct-v0_2024-06-26T21_49_03.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/services_agreement/reasoning/train_Mixtral-8x7B-Instruct-v0_2024-06-26T21_49_03.jsonl
 compositional_skills/writing/freeform/poetry/ode/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/writing/freeform/poetry/ode/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/writing/freeform/poetry/ode --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T21:59:28Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/writing/freeform/poetry/ode/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 21:59:36,621 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->poetry->ode
 [31mGenerating dataset failed with the following error: There was a problem with the new data, please make sure the yaml is formatted correctly, and there is enough new data(2+ Q&A))[0m

  0% 0/100 [00:00<?, ?it/s]
 compositional_skills/writing/freeform/prose/emails/informal/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/writing/freeform/prose/emails/informal/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/writing/freeform/prose/emails/informal --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T21:59:37Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/writing/freeform/prose/emails/informal/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 21:59:45,818 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->prose->emails->informal
 [31mGenerating dataset failed with the following error: There was a problem with the new data, please make sure the yaml is formatted correctly, and there is enough new data(2+ Q&A))[0m

  0% 0/100 [00:00<?, ?it/s]
 compositional_skills/extraction/technical_paper/abstract/csv/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/extraction/technical_paper/abstract/csv/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/technical_paper/abstract/csv --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T21:59:46Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/extraction/technical_paper/abstract/csv/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 21:59:54,996 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Identify and summarize in csv format the different types of DP synthetic data generation mechanisms mentioned in the abstract.
 I> Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> Type, Description
 GAN-based, A technique that uses Generative Adversarial Networks (GANs) to generate synthetic data.
 Marginal-based, A technique that preserves marginal distributions while generating synthetic data.
 Workload-based, A technique that optimizes for worst-case error over a distribution of queries.

 Q> Explain the main challenges of task-agnostic private synthetic data generation methods in .csv format.
 I> 
 A> Challenge, Explanation
 Variability, Different downstream tasks have different requirements making it difficult for task-agnostic methods to address all of them.
 Lack of awareness, Task-agnostic methods are not aware of the downstream tasks leading to reduced utility.
 Expense, Addressing all requirements of end users may be costly and time-consuming.


  2% 2/100 [00:11<09:24,  5.76s/it]INFO 2024-06-26 22:00:06,511 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Identify the method for private synthetic data generation that incorporates downstream task information in a .csv format.
 I> Some of the recent DP synthetic data generation mechanisms include GAN-based, marginal-based, and workload-based methods. These methods aim to generate private synthetic data that is task-agnostic, meaning they do not consider the requirements of downstream tasks in the data generation process.
 A> Method, Explanation
 Task-aware synthetic data generation, This method takes into account the requirements of downstream tasks, leading to improved utility.

 Q> Summarize the key contributions of the research paper in 100 words or less in a .csv format.
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab

 ## Abstract

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> Key Contribution, Explanation
 Private synthetic data post-processing, A post-processing technique is introduced to improve the utility of private synthetic data for specific downstream tasks.
 Preserving strong privacy guarantees, The post-processing technique does not compromise the privacy guarantees of the synthetic data.
 Improving dataset quality, The post-processing technique improves the quality of the synthetic data while preserving a certain level of utility.


  4% 4/100 [00:23<09:35,  6.00s/it]INFO 2024-06-26 22:00:18,839 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Name the authors of the research paper.
 I> 
 A> Authors: Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava

 Q> Describe the main problem addressed by the authors in the research paper in 100 words or less.
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use.
 A> The research paper addresses the problem that existing algorithms for private synthetic data generation are oblivious to the specific requirements of downstream tasks, which can significantly reduce the utility of the data.


  6% 6/100 [00:33<08:33,  5.47s/it]INFO 2024-06-26 22:00:28,506 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 INFO 2024-06-26 22:00:30,239 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Identify the number of authors that contributed to the paper "A machine learning approach for predicting COVID-19 mortality: an analysis of 25,948 patients from multiple centers in China and Italy."
 I> ## A machine learning approach for predicting COVID-19 mortality: an analysis of 25,948 patients from multiple centers in China and Italy.
 > 

 Yu-Chuan Shih,1,4,∗,5,6 Masoud Ghafoorian,1,4,∗,5 Dan Wu,2,4,∗,5 

 Ximei Wang,2,4,∗,5 Weizhi Qian,3,4,∗

 Tingting He,1,4 Chong Sun,1,4,7

 Peng Yin,3,4,7 Lina Wang,2,4,7 

 Jinfeng Huang,2,4,8 Binbin Wang,2,4,8

 Yong Liu,1,4 Xinlei Chen,1,4 

 Feng Zhang,1,4 Tingting Xie,1,4 

 Xingyu Kong,1,4 Weijie Hao,2,4 

 Dan Guan,1,4 Ting Yue,3,4 

 Zhiping Liu,1,4 Gengsheng Wu,2,4 

 Xia Zhang,3,4 Yandong Li,2,4,9

 Liming Cao,3,4 Xiao Chen,3,4 

 Xiaohua Yang,3,4 Yi Sheng,2,4

 Min Yang,3,4 Jiaxing Wu,2,4 

 Jian Wang,3,4 Guihong Qiu,2,4 

 Xiangdong Li,3,4 Zhuoran Qiu,2,4 

 Anfeng Liu,1,4 Cheng Wang,3,4
 ## Abstract

 * Background: Predicting the mortality of COVID-19 patients is crucial for monitoring and treating patients effectively. * Methods: We collected data from 25,948 patients from three centers in China and two centers in Italy. We analyzed demographical, radiological, laboratory, and mortality data using statistical analysis and machine learning techniques to identify factors associated with mortality. We also developed a risk model to predict the mortality in COVID-19 patients. * Results: Demographical factors, radiological features, laboratory test results, and some complications were significantly associated with mortality in COVID-19 patients. The risk model developed using machine learning techniques accurately predicted the mortality in COVID-19 patients. * Conclusion: The risk model can help in monitoring and treating patients affected by COVID-19.
 A> 4

 Q> From the paper "A machine learning approach for predicting COVID-19 mortality: an analysis of 25,948 patients from multiple centers in China and Italy.", list down all the methods used in analyzing the data.
 I> 
 A> Method
 Statistical analysis
 Machine learning techniques


  8% 8/100 [00:50<10:04,  6.57s/it]INFO 2024-06-26 22:00:45,042 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Determine the frequency of terms 'private synthetic data generation' and 'downstream use cases' in the abstract and introduction. Return the output in csv format.
 I> <noinput>

 ## Abstract

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.

 ## 1 Introduction

 The advancement of machine learning (ML) techniques relies on large amounts of training data. However, data collection also poses a significant risk of exposing private information. In recent years, several instances of privacy breaches have surfaced [NS06, Con18], making it urgent to find a reliable way to share data. Today, the de facto standard for privacy protection is differential privacy (DP) [DR14]. DP ensures that useful information of a private dataset can be released while simultaneously preventing adversaries from identifying individuals' personal data. DP has been utilized effectively in a wide variety of settings, by actors including the US Census [Abo18] and various large corporations [App17, Fac20, RE19, HBMAL19, IBM23].

 Generating private synthetic data is a crucial application of DP. It allows data scientists to train their ML models on the synthetic data while preserving a certain level of utility when deploying these models on real test data. The U.S. National Institute of Standards and Technology (NIST) has emphasized its significance by hosting a series of competitions [RTMT21, MMS21]. There is also significant work introducing new DP synthetic data generation mechanisms, including GAN-based [XLW + 18, BJWW + 19, JYVDS19, TWB + 19], marginal-based [ZCP + 17, MSM19, MMS21], and workload-based [VTB + 20, ABK + 21, LVW21, MMSM22, VAA + 22] methods. Existing methods for generating private synthetic data are task-agnostic-they do not take into account the downstream use cases of the synthetic data in the data generation process. However, end users often have specific requirements for synthetic datasets to be successfully analyzed by their existing data science pipelines, which are often well-established, well-understood, heavily vetted, and difficult or expensive to change. Unfortunately, synthetic data generated by existing methods may not always meet these requirements, resulting in reduced utility for their downstream use cases. This raises a fundamental question:
 A> Term,Frequency
 Private synthetic data generation,3
 Downstream use cases,2


  9% 9/100 [01:01<11:27,  7.55s/it]INFO 2024-06-26 22:00:56,081 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 INFO 2024-06-26 22:00:59,209 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Outline the methods employed in the technical paper.
 I> Utilization of machine learning techniques for predicting the mortality of COVID-19 patients: an analysis of 25,948 patients in China and Italy.
 > 

 In this study, the research team collected demographical, radiological, laboratory, and mortality data from 25,948 patients from three centers in China and two centers in Italy. They utilized statistical analysis and machine learning techniques to analyze the data, and develop a risk model to predict the mortality in COVID-19 patients.
 A> 1. Data collection from 25,948 patients in China and Italy.
 2. Utilization of statistical analysis for identifying factors associated with mortality.
 3. Employment of machine learning techniques for predicting mortality.
 4. Development of a risk model for predicting the mortality in COVID-19 patients.

 Q> Highlight the major findings of the research.
 I> Analysis of 25,948 COVID-19 patients in China and Italy reveals key factors associated with mortality and provides a means for predicting the mortality rate.
 > 

 The research found that demographical factors, radiological features, laboratory test results, and some complications were significantly associated with mortality in COVID-19 patients. The risk model developed using machine learning techniques accurately predicted the mortality in COVID-19 patients.
 A> 1. Demographical factors, radiological features, laboratory test results, and some complications are significantly associated with mortality in COVID-19 patients.
 2. A risk model developed using machine learning techniques accurately predicts mortality in COVID-19 patients.


 11% 11/100 [01:15<11:04,  7.47s/it]INFO 2024-06-26 22:01:10,751 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Identify the authors of the research paper and their affiliations.
 I> 
 A> Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab

 Q> Summarize the research paper's abstract in less than 100 words.
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab

 ## Abstract

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality.
 A> The authors propose a post-processing technique to enhance the utility of private synthetic data for specific end-user requirements while preserving dataset quality and privacy guarantees.


 13% 13/100 [01:26<09:40,  6.68s/it]INFO 2024-06-26 22:01:21,225 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 INFO 2024-06-26 22:01:23,584 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Identify the researchers involved in the paper and their affiliations.
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab
 A> The researchers involved in the paper are Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, and Akash Srivastava, and they are affiliated with the MIT-IBM Watson AI Lab.


 14% 14/100 [01:35<10:11,  7.11s/it]INFO 2024-06-26 22:01:30,025 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> List the benchmark datasets used in the study.
 I> 
 A> Datasets: Adult Income, German Credit, Loan Default


 15% 15/100 [01:40<09:42,  6.85s/it]INFO 2024-06-26 22:01:35,979 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Specify the data generation methods and criteria used in the evaluation of the private synthetic data.
 I> ## An Empirical Evaluation of Private Synthetic Data for Data Publication

 Arvind Narayanan, Rachel Cummings, Steven Wu

 ## Abstract

 Private synthetic data is increasingly being generated and released by companies and governments to protect individual privacy while allowing for public access to the information contained in the original dataset. We conduct an empirical evaluation of a wide range of synthetic data generation methods across multiple benchmark datasets for data publication and share our findings with respect to privacy, utility and computational cost. Our results show that using methods rooted in machine learning tend to offer better utility and precision than their non-machine learning counterparts, and that differentially private methods generally offer strong privacy guarantees. However, evaluating these methods is often impeded by the lack of testing standards for synthetic data, and the limited availability of well-documented benchmark datasets. We provide an overview of the challenges in generating private synthetic data, and propose a set of guidelines and best practices for generating synthetic data for data publishing.
 A> Method, Criteria
 Machine learning based, Utility, Precision
 Differentially private, Privacy

 Q> List the datasets and the methods used in evaluating the utility of private synthetic data.
 I> 
 A> Dataset, Method
 Adult dataset, Machine learning based method
 Credit dataset, Machine learning based method
 Income dataset, Differentially private method
 Loan dataset, Differentially private method


 17% 17/100 [01:52<08:44,  6.33s/it]INFO 2024-06-26 22:01:47,000 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Determine the methodology or techniques used in the research.
 I> A new deep learning model that incorporates domain-specific knowledge into the training process to improve image classification accuracy is presented.
 A> The researchers developed a new deep learning model that incorporates domain-specific knowledge into the training process to improve image classification accuracy.

 Q> Present the main problem or topic of the research.
 I> Investigating the use of synthetic data in machine learning for privacy protection while maintaining high data utility.
 A> The main problem or topic of the research is investigating the use of synthetic data in machine learning for privacy protection while maintaining high data utility.


 19% 19/100 [02:01<07:44,  5.73s/it]INFO 2024-06-26 22:01:56,353 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 INFO 2024-06-26 22:01:59,023 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Describe the overall objective and key takeaways of the research paper.
 I> ## Private Data Synthesis using Differential Privacy

 The objective of this research paper is to explore privacy-preserving data synthesis using differential privacy. The key takeaway is that the proposed approach improves data utility while maintaining strong differential privacy guarantees, as demonstrated through extensive evaluation on multiple real-world datasets.
 A> The overall objective of the "Private Data Synthesis using Differential Privacy" research paper is to address the challenge of privacy-preserving data synthesis by utilizing differential privacy methods. The authors demonstrate that their proposed approach enhances data utility and maintains strong privacy guarantees across various real-world datasets, offering a significant advancement in private synthetic data generation.

 Q> What are the main issues addressed by the authors regarding private synthetic data generation?
 I> 
 A> The main issues addressed by the authors are data privacy preservation, data utility enhancement, and maintaining differential privacy guarantees during the synthesis of private datasets, all of which are crucial challenges in the realm of data sharing and analysis.


 21% 21/100 [02:14<07:50,  5.96s/it]INFO 2024-06-26 22:02:09,125 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Summarize the main topic of the research paper in one sentence.
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab

 ## Abstract

 [...]

 ## 1 Introduction

 [...]
 A> The paper discusses a post-processing technique to improve the utility of synthetic data for specific downstream tasks while preserving strong privacy guarantees and dataset quality.

 Q> Provide the main benefits of the proposed solution in the research paper.
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab

 ## Abstract

 [...]

 ## 1 Introduction

 [...]

 ** Section 1 (Introduction)
 The advancement of machine learning (ML) techniques relies on large amounts of training data. However, data collection poses a significant risk of exposing private information. In recent years, several instances of privacy breaches have surfaced [NS06, Con18], making it urgent to find a reliable way to share data. Today, the de facto standard for privacy protection is differential privacy (DP) [DR14]. DP ensures that useful information of a private dataset can be released while simultaneously preventing adversaries from identifying individuals' personal data. DP has been utilized effectively in a wide variety of settings, by actors including the US Census [Abo18] and various large corporations [App17, Fac20, RE19, HBMAL19, IBM23]. Generating private synthetic data is a crucial application of DP. It allows data scientists to train their ML models on the synthetic data while preserving a certain level of utility when deploying these models on real test data. The U.S. National Institute of Standards and Technology (NIST) has emphasized its significance by hosting a series of competitions [RTMT21, MMS21]. There is also significant work introducing new DP synthetic data generation mechanisms, including GAN-based [XLW + 18, BJWW + 19, JYVDS19, TWB + 19], marginal-based [ZCP + 17, MSM19, MMS21], and workload-based [VTB + 20, ABK + 21, LVW21, MMSM22, VAA + 22] methods. Existing methods for generating private synthetic data are task-agnostic-they do not take into account the downstream use cases of the synthetic data in the data generation process. However, end users often have specific requirements for synthetic datasets to be successfully analyzed by their existing data science pipelines, which are often well-established, well-understood, heavily vetted, and difficult or expensive to change. Unfortunately, synthetic data generated by existing methods may not always meet these requirements, resulting in reduced utility for their downstream use cases.
 A> The main benefits of the proposed solution include improving the utility of synthetic data for specific downstream tasks, preserving strong privacy guarantees and dataset quality, and emphasizing the significance of generating private synthetic data in various settings highlighted by the U.S. National Institute of Standards and Technology (NIST) and large corporations.


 23% 23/100 [02:29<08:26,  6.57s/it]INFO 2024-06-26 22:02:24,828 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 INFO 2024-06-26 22:02:26,493 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> What are the key findings or results presented in the paper?
 I> 
 A> The key findings of the paper are that the proposed method of combining feature selection techniques improves the classification accuracy of highly imbalanced datasets.

 Q> Summarize the objectives of the research outlined in the abstract.
 I> ## Real-time Prediction of Video Quality for Lossy Compression Using Deep Learning

 The goal of this research is to develop a real-time video quality scalable deep learning model for lossy compression.
 A> The objective of the research is to develop a real-time video quality scalable deep learning model for lossy compression that can predict and optimize the video quality for different compression levels.


 25% 25/100 [02:40<07:47,  6.24s/it]INFO 2024-06-26 22:02:35,858 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Identify the research gap addressed in the paper.
 I> 
 A> The research gap addressed in the paper is the lack of post-processing techniques for private synthetic data generation algorithms to improve their utility for downstream tasks, while preserving privacy guarantees and dataset quality.

 Q> Summarize the main contribution of the paper in one sentence.
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab
 A> The paper introduces a post-processing technique that improves the utility of synthetic data for selected measures, while preserving strong privacy guarantees and dataset quality.


 27% 27/100 [02:50<07:02,  5.78s/it]INFO 2024-06-26 22:02:45,426 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> List the benchmark datasets used in the empirical evaluation of synthetic data generation methods for data publication.
 I> <noinput>

 ## An Empirical Evaluation of Private Synthetic Data for Data Publication

 Arvind Narayanan, Rachel Cummings, Steven Wu

 ## Abstract

 Private synthetic data is increasingly being generated and released by companies and governments to protect individual privacy while allowing for public access to the information contained in the original dataset. We conduct an empirical evaluation of a wide range of synthetic data generation methods across multiple benchmark datasets for data publication and share our findings with respect to privacy, utility and computational cost. Our results show that using methods rooted in machine learning tend to offer better utility and precision than their non-machine learning counterparts, and that differentially private methods generally offer strong privacy guarantees. However, evaluating these methods is often impeded by the lack of testing standards for synthetic data, and the limited availability of well-documented benchmark datasets. We provide an overview of the challenges in generating private synthetic data, and propose a set of guidelines and best practices for generating synthetic data for data publishing.

 ## Benchmark Datasets
 <noinput>
 A> name
 Adult Census Income Dataset
 Credit Approval Dataset
 German Credit Dataset
 Heart Disease Dataset
 HIV Dataset
 Immunotherapy Dataset
 KDD Cup 1999 Dataset
 Netflix Prize Dataset

 Q> What are the specific challenges in generating private synthetic data for data publication?
 I> <noinput>

 ## An Empirical Evaluation of Private Synthetic Data for Data Publication

 Arvind Narayanan, Rachel Cummings, Steven Wu

 ## Abstract

 Private synthetic data is increasingly being generated and released by companies and governments to protect individual privacy while allowing for public access to the information contained in the original dataset. We conduct an empirical evaluation of a wide range of synthetic data generation methods across multiple benchmark datasets for data publication and share our findings with respect to privacy, utility and computational cost. Our results show that using methods rooted in machine learning tend to offer better utility and precision than their non-machine learning counterparts, and that differentially private methods generally offer strong privacy guarantees. However, evaluating these methods is often impeded by the lack of testing standards for synthetic data, and the limited availability of well-documented benchmark datasets. We provide an overview of the challenges in generating private synthetic data, and propose a set of guidelines and best practices for generating synthetic data for data publishing.
 A> The challenges in generating private synthetic data for data publication include the lack of testing standards, which makes it difficult to evaluate different methods, and the limited availability of well-documented benchmark datasets for testing the synthetic data generation methods.


 29% 29/100 [03:04<07:14,  6.12s/it]INFO 2024-06-26 22:02:59,402 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Explain the methods used to assess the utility of the synthetic datasets generated in the study.
 I> In this study, we used Gini Index, Statistical Distance, and Dependency Measure as evaluation metrics to measure utility.

 ## Abstract

 We present a compositional framework to generate synthetic tabular data that allows for the precise expression of utility and privacy guarantees. Using this framework, we evaluate and compare multiple release mechanisms on three different metrics.
 A> The Gini Index, Statistical Distance, and Dependency Measure were used to assess the utility of the synthetic datasets generated. These metrics evaluate how well the synthetic datasets preserve the statistical properties and relationships among attributes in the original datasets. This information is important to ensure that the synthetic datasets are useful for research and analysis purposes while preserving privacy guarantees.

 Q> What are the different synthetic data release mechanisms evaluated in the study?
 I> The release mechanisms evaluated in the study include Local Randomization, Data Cubes, and Data Synthesizers.

 ## Abstract

 We present a compositional framework to generate synthetic tabular data that allows for the precise expression of utility and privacy guarantees. Using this framework, we evaluate and compare multiple release mechanisms on three different metrics.
 A> The different synthetic data release mechanisms evaluated in the study are Local Randomization, Data Cubes, and Data Synthesizers. These mechanisms were chosen for their relevance and applicability to the problem of generating synthetic tabular data.


 31% 31/100 [03:15<06:52,  5.97s/it]INFO 2024-06-26 22:03:10,474 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 INFO 2024-06-26 22:03:12,607 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Extract the experimental settings of the paper, including the evaluation metric and the hyperparameters.
 I> Evaluation metric: accuracy; Hyperparameters: learning rate=0.01, batch size=64
 A> Metric, Value
 Accuracy, 0.01
 Batch size, 64

 Q> Identify the advanced techniques applied in the paper.
 I> Techniques: Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Federated Learning (FL)
 A> Technique
 Generative Adversarial Networks (GANs)
 Variational Autoencoders (VAEs)
 Federated Learning (FL)


 33% 33/100 [03:27<06:36,  5.91s/it]INFO 2024-06-26 22:03:22,007 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 INFO 2024-06-26 22:03:23,627 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Concisely summarize the problem addressed in the paper, as well as the proposed solution, approach, or methodology.
 I> 
 A> The paper tackles the issue of unreliable semantic segmentation in medical imaging. It presents a novel CNN architecture that incorporated attention gates, significantly improving segmentation accuracy.

 Q> Identify the data sources used for the research and specify the size or scope of these datasets.
 I> Data sources: ImageNet, COCO; ImageNet: 1.2 million images, 1000 classes, 5000 images per class; COCO: 328K images, 80 object categories, 5 captions per image
 A> Source, Description
 ImageNet, Contains 1.2 million images across 1000 classes with 5000 images per class.
 COCO, Comprises 328K images categorized under 80 different object categories and includes 5 captions per image.


 35% 35/100 [03:38<06:22,  5.88s/it]INFO 2024-06-26 22:03:33,640 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 INFO 2024-06-26 22:03:35,631 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Identify the dataset(s) used in this research and outline their relevance to the study.
 I> ## Improved Traffic Prediction Using Multi-source Data and LSTM Neural Networks

 The study relied on four datasets: (1) taxi-trip data, (2) taxi-OD data, (3) road networks, and (4) real-time traffic information.
 A> The datasets used in the study are taxi-trip data, taxi-OD data, road networks, and real-time traffic information, which provide essential information for improving traffic prediction by utilizing multi-source data and LSTM neural networks.

 Q> Extract the names of any proposed algorithms, methods, or techniques outlined in the abstract.
 I> ## Fast and Accurate 3D Point Cloud Classification: A Lightweight Network with Dual Attention and Feature Recalibration

 The proposed method is a lightweight network incorporating dual attention and feature recalibration techniques for accurate and fast 3D point cloud classification.
 A> The proposed algorithm, method, or technique in the abstract is a lightweight network featuring dual attention and feature recalibration techniques for accurate and fast 3D point cloud classification.


 37% 37/100 [03:51<06:16,  5.97s/it]INFO 2024-06-26 22:03:46,006 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Which synthetic data generation algorithms were tested in the study?
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab
 A> <noinput>
 The study does not provide specific information about the synthetic data generation algorithms that were tested.


 38% 38/100 [04:01<06:55,  6.69s/it]INFO 2024-06-26 22:03:56,040 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Which methods for synthetic data generation are compared in the empirical evaluation?
 I> 
 A> The methods compared in the empirical evaluation are categorized as machine learning methods and non-machine learning methods. Examples of machine learning methods include GANs (Generative Adversarial Networks) and PATE (Private Aggregation of Teacher Ensembles). Examples of non-machine learning methods include data swapping and data microaggregation.

 Q> How do the authors measure the privacy guarantees provided by the evaluated methods?
 I> 
 A> The authors measure the privacy guarantees provided by the evaluated methods using differentially private methods. They assess the extent to which the information about individual records is protected, and verify if the methods avoid the leakage of sensitive information.


 40% 40/100 [04:10<06:03,  6.05s/it]INFO 2024-06-26 22:04:05,614 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Identify the key challenge addressed in the paper.
 I> 
 A> The main challenge addressed is the lack of alignment between existing private synthetic data generation methods and end users' specific requirements for synthetic datasets.

 Q> Describe the primary technique employed to address the challenge.
 I> 
 A> The paper introduces a post-processing technique, which involves resampling from the synthetic data using an efficient stochastic first-order algorithm to find optimal resampling weights for improving the utility of synthetic data with respect to the end user's selected utility measures.


 42% 42/100 [04:19<05:22,  5.56s/it]INFO 2024-06-26 22:04:14,683 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 INFO 2024-06-26 22:04:20,060 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> What measures were used to evaluate the performance of the data generation techniques in the study?
 I> ## Metrics

 We evaluate the performance of our approach using the following three metrics:

 1. Average utility of downstream models trained on the synthetic data.
 2. Privacy guarantees, characterized by strong privacy parameters (ε, δ).
 3. Robustness against different adversaries and attacks.

 These measures were used to compare and evaluate the performance of our technique against other state-of-the-art mechanisms.

 ## Experimental Setting

 We conducted comprehensive numerical experiments using five benchmark datasets and six different synthetic data generation algorithms. We used the following two settings:

 1. "Offline setting": We fixed the private parameter ε and generated synthetic data in advance for each algorithm.
 2. "Online setting": We generated synthetic data on-the-fly, adaptively changing the private parameter ε based on the observed data distributions.
 A> The measures used to evaluate the performance of the data generation techniques in the study are average utility of downstream models trained on the synthetic data, privacy guarantees characterized by strong privacy parameters (ε, δ), and robustness against different adversaries and attacks. These measures were used to compare and evaluate the performance of the technique against other state-of-the-art mechanisms.

 Q> What were the best-performing data generation mechanisms in the offline setting of the study?
 I> 
 A> The best-performing data generation mechanisms in the offline setting of the study were the Data Synthesizer (DS) and the generative adversarial network (GAN)-based algorithms. These mechanisms consistently showed superior performance across multiple benchmark datasets and utility measures in the offline setting.


 44% 44/100 [04:36<06:02,  6.48s/it]INFO 2024-06-26 22:04:31,606 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Summarize the abstract's key points and present them in tabular format.
 I> **Abstract**
 This paper proposes a new approach for generating synthetic data while maintaining theoretical guarantees on privacy. We use our framework to generate synthetic microdata for two public datasets and demonstrate that it preserves the utility of the original data on various data-analytic tasks.
 A> | Key Points | Description |
 | --- | --- |
 | Proposed Approach | New approach for generating synthetic data |
 | Privacy Guarantees | Theoretical guarantees are maintained |
 | Framework Demonstration | Generates synthetic microdata for two public datasets |
 | Utility Preservation | Utility of original data preserved for data-analytic tasks |

 Q> Is a dataset used in the experimentation process mentioned and clearly specified?
 I> 
 A> The information provided in the abstract is insufficient to determine if a specific dataset is mentioned or clearly specified. You should consult the full text of the technical paper for a clear answer.


 46% 46/100 [04:46<05:25,  6.03s/it]INFO 2024-06-26 22:04:41,658 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Name the state-of-the-art synthetic data generation algorithms mentioned in the abstract.
 I> 
 A> Algorithm
 DP-MERF
 GAN-DP
 DPCopulaGAN
 DP-SYN

 Q> Describe how the authors enhanced the utility of private synthetic data.
 I> 
 A> The authors introduced a post-processing technique that resamples from the synthetic data, filtering out samples that do not meet selected utility measures through an efficient stochastic first-order algorithm.


 48% 48/100 [04:55<04:48,  5.55s/it]INFO 2024-06-26 22:04:50,620 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Provide the results of the performed experiment in a tabular format.
 I> 
 A> | Experiment | Utility Score | Privacy Score |
 | --- | --- | --- |
 | Experiment 1 | 0.82 | 0.85 |
 | Experiment 2 | 0.87 | 0.81 |
 | Experiment 3 | 0.84 | 0.83 |

 Q> Identify the five major challenges the paper tries to tackle.
 I> 
 A> 1. Maximizing data utility while preserving privacy
 2. Handling sensitivity to intruders
 3. Meeting digital forensic requirements
 4. Ensuring regulatory compliance
 5. Maintaining syntactic and semantic consistency


 50% 50/100 [05:05<04:26,  5.34s/it]INFO 2024-06-26 22:05:00,334 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> List the centers from where the data was collected for the COVID-19 mortality prediction study.
 I> <noinput>

 ## Abstract

 We collected data from 25,948 patients from three centers in China and two centers in Italy.
 A> The data was collected from three centers in China and two centers in Italy.

 Q> What are the machine learning techniques that were used in the COVID-19 mortality prediction study?
 I> <noinput>

 ## Abstract

 We analyzed demographical, radiological, laboratory, and mortality data using statistical analysis and machine learning techniques to identify factors associated with mortality. We also developed a risk model to predict the mortality in COVID-19 patients.
 A> The machine learning techniques used in the COVID-19 mortality prediction study include statistical analysis and the development of a risk model to predict the mortality in COVID-19 patients.


 52% 52/100 [05:15<04:10,  5.22s/it]INFO 2024-06-26 22:05:10,222 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Explain the method used for the data preprocessing step.
 I> ## Predicting Heart Disease: Analysis and Comparison of Machine Learning Algorithms

 The raw data went through a preprocessing step where missing values were imputed, and the data was standardized.
 A> The method used for the data preprocessing step involved imputing missing values and standardizing the raw data. This ensured that the data was consistent and that the machine learning algorithms could learn from it effectively.

 Q> What were the results of the evaluation of the proposed solution?
 I> 
 A> The evaluation of the proposed solution was successful, with the solution significantly outperforming the baseline solution in terms of accuracy and efficiency. The proposed solution achieved an accuracy of 92.3%, compared to the baseline solution's accuracy of 85.1%, and also demonstrated improved computational efficiency.


 54% 54/100 [05:24<03:55,  5.12s/it]INFO 2024-06-26 22:05:19,987 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Identify the authors and their affiliations mentioned in the abstract.
 I> ## Efficient Video Outdoor Scene Parsing via Spatio-Temporal Graph Attention Network

 Yang Lu, Kai Li, Huiling Liao, and Zhennan Huang

 CASIA, Chinese Academy of Sciences, Beijing 100190, China

 In this paper, we propose a novel deep learning model, Spatio-Temporal Graph Attention Network (ST-GAT), for video scene parsing. The ST-GAT model effectively learns the spatio-temporal context information under complex and diverse outdoor environments. Extensive experiments on public datasets demonstrate that our approach achieves significant improvement over state-of-the-art methods in both speed and accuracy.
 A> The authors of the paper are Yang Lu, Kai Li, Huiling Liao, and Zhennan Huang, who are affiliated with CASIA, Chinese Academy of Sciences, Beijing 100190, China.

 Q> Describe the problem being addressed in the research paper.
 I> 
 A> The problem being addressed in the research paper is that existing private synthetic data generation algorithms are agnostic to downstream tasks, and end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use.


 56% 56/100 [05:35<03:49,  5.22s/it]INFO 2024-06-26 22:05:30,892 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 INFO 2024-06-26 22:05:35,200 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> What were the main findings regarding the performance of deep reinforcement learning (DRL) in the given study?
 I> ## Reinforcement Learning for Resource Management in Wireless Networks

 The study revealed that DRL outperformed traditional approaches by efficiently managing resources and improving network performance.
 A> The main findings of the study showed that deep reinforcement learning (DRL) significantly outperformed traditional resource management approaches in wireless networks by efficiently managing resources and improving network performance.

 Q> Extract the details about the model structure and its primary relevance to the study.
 I> ## Recommendation Systems with Graph-based Embeddings for Feature Learning and Click Prediction

 A graph convolutional matrix completion (GC-MC) model was employed that used graph-based embeddings to improve feature learning and click prediction.
 A> The model structure used in the study is the graph convolutional matrix completion (GC-MC) model. This model employs graph-based embeddings to enhance feature learning and click prediction, making it more effective in recommendation systems compared to traditional approaches.


 58% 58/100 [05:50<04:03,  5.81s/it]INFO 2024-06-26 22:05:45,224 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> What analytic tasks were applied to evaluate the generated synthetic data?
 I> See the abstract: "We use our framework to generate synthetic microdata for two public datasets and demonstrate that it preserves the utility of the original data on various data-analytic tasks."
 A> The data-analytic tasks involve evaluating the performance of the synthetic data compared to the original data on various analytical methods.

 Q> Find the two public datasets used in the research paper.
 I> 
 A> Two public datasets used are not specified in the abstract. The abstract states, "We use our framework to generate synthetic microdata for two public datasets."


 60% 60/100 [05:59<03:38,  5.45s/it]INFO 2024-06-26 22:05:54,505 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Identify the datasets used in the study and list them in a .csv format.
 I> * Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 * Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab
 * Abstract

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> Name of Dataset
 Benchmark Dataset 1
 Benchmark Dataset 2
 Benchmark Dataset 3

 Q> What are the metrics used to evaluate the performance of the proposed technique?
 I> 
 A> The metrics used to evaluate the performance of the proposed technique are utility score and privacy score.


 62% 62/100 [06:10<03:28,  5.50s/it]INFO 2024-06-26 22:06:05,692 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Extract the proposed method's name and the problem it addresses from the abstract.
 I> ## Predicting Microbial Functionality using Deep Learning: A Computational Approach

 A novel computational approach for predicting microbial functionality using deep learning is proposed in this paper. We introduce a deep learning-based method that effectively utilizes large-scale microbial sequencing data to predict microbial functionalities. The proposed approach outperforms traditional methods and provides new insights into microbial communities.
 A> The proposed method is called "Predicting Microbial Functionality using Deep Learning," and it addresses the problem of predicting microbial functionalities using a deep learning-based approach.

 Q> Identify the evaluation metrics and the results of the proposed method mentioned in the abstract.
 I> ## Real-Time Video Object Detection on Embedded Platforms

 We present a real-time video object detection method on embedded platforms using deep learning. Our method achieves an average precision of 75% and a processing speed of 30 frames per second on a NVIDIA Jetson TX1 platform. The method outperforms previous state-of-the-art approaches in terms of speed and accuracy.
 A> The evaluation metrics used are average precision and processing speed, and the results are 75% and 30 frames per second, respectively.


 64% 64/100 [06:21<03:16,  5.45s/it]INFO 2024-06-26 22:06:16,346 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Can you identify the dependent and independent variables in the described experiment?
 I> The abstract states: "We investigated the effect of adjusting the temperature on the yield of the reaction, finding consistent improvements across multiple samples."
 A> Based on the abstract's information, the dependent variable would be the yield of the reaction, whereas the independent variable is the temperature setting.

 Q> What are the performance metrics used in the evaluation of the proposed method?
 I> 
 A> The abstract does not offer specific information on the performance metrics used to evaluate the proposed method. You should refer to the full text for a comprehensive answer.


 66% 66/100 [06:30<02:56,  5.18s/it]INFO 2024-06-26 22:06:25,479 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Describe the process of adversarial training for semi-supervised data in .csv format.
 I> 
 A> Step, Description
 Labeled Data Preparation, Labeled data points are selected along with their corresponding perturbations.
 Model Training, A model is trained using labeled and adversarial data to minimize loss and increase robustness.
 Loss Function Optimization, Loss is optimized through backward propagation and weight updates.
 Prediction, Predictions are obtained on the validation set.


 67% 67/100 [06:37<02:58,  5.42s/it]INFO 2024-06-26 22:06:32,011 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Identify key limitations or weaknesses of the method proposed in the research paper.
 I> ## Genomic Privacy with Synthetic Haplotypes

 Matthew Joseph, Chen-Kai Liu, Karen Zheng, Kobbi Nissim

 ## Abstract

 [...] Genomic privacy can, today, be protected using techniques like synthetic haplotypes generation. However, current techniques are not **provably** private. 

 ** Section 1 (Introduction)
 Genomic privacy is a growing concern as genomic sequencing becomes increasingly common. Recently, there has been a spate of breaches involving de-identified patient genomic information [RP13, Gas19]. Clearly, current solutions do not suffice to protect genomic privacy. Fortunately, synthetic haplotypes, which are privatized genomic sequences generated using differential privacy, provide a promising alternative to share genomic data. Synthetic haplotypes can preserve all scientifically relevant information about the sample, while adding strategic noise to obscure the identities of the individuals in the sample. Previous work suggests that synthetic haplotypes can effectively protect genomic privacy [GJSW19, INT13, KMP15], but is unable to provide **formal** privacy guarantees. [...]
 A> The key limitations or weaknesses of the method proposed in the research paper involve the lack of formal, rigorously provable privacy guarantees provided by the synthetic haplotypes technique. This merits further investigation to strengthen the privacy guarantees and ensure the optimal practical application of the approach.

 Q> List the main contributions or innovations in the research paper.
 I> 
 A> The main contributions or innovations in the research paper include the introduction of a novel machine learning algorithm for anomaly detection, which outperforms state-of-the-art techniques in terms of accuracy and efficiency. The authors apply their proposed approach to various real-world datasets to demonstrate its effectiveness.


 69% 69/100 [06:48<02:53,  5.60s/it]INFO 2024-06-26 22:06:43,946 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Present the list of authors and their affiliation.
 I> 
 A> Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, and Akash Srivastava; MIT-IBM Watson AI Lab

 Q> State the main objectives of the study.
 I> 
 A> The main objectives of the study are developing a post-processing technique for private synthetic data generation algorithms, improving the utility of synthetic data concerning end-users' selected measures, and preserving strong privacy guarantees and dataset quality.


 71% 71/100 [06:57<02:32,  5.25s/it]INFO 2024-06-26 22:06:52,992 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Find the table in the paper comparing the accuracy of models A, B, and C by reporting their F1 scores.
 I> 
 A> In Table 1, the F1 scores of models A, B, and C are reported under the "F1 Score" column. Model A has a score of 0.92, Model B has a score of 0.88, and Model C has a score of 0.86.

 Q> Extract the findings of the conducted user study on the proposed algorithm's effectiveness.
 I> 
 A> The user study revealed that the proposed algorithm outperformed existing methods regarding both execution time and accuracy. Specifically, the proposed algorithm had an average execution time of 24.3 seconds and an accuracy of 89.5%, while existing methods had higher execution times and lower accuracy rates.


 73% 73/100 [07:07<02:18,  5.12s/it]INFO 2024-06-26 22:07:02,681 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> What are the key features of the proposed system or methodology?
 I> ## Proposed System: A Machine Learning-based Approach for Text-to-SQL System

 The proposed system uses a two-stage machine learning-based approach for text-to-SQL systems: a ranking model that selects the top candidate, and a reinforced model that refines the candidate to generate the final SQL query.
 A> The key features of the proposed system include a two-stage machine learning-based approach that combines ranking and reinforced models to improve text-to-SQL systems' accuracy and performance.


 74% 74/100 [07:13<02:16,  5.26s/it]INFO 2024-06-26 22:07:08,551 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> How is the paper's proposed method evaluated?
 I> 
 A> The proposed method is evaluated through a series of experiments, including a one-time simulation for each of the eleven scenarios, a cross-validation procedure that uses each original stream and its corresponding hybrid stream, and a comparison between the proposed method and existing approaches.

 Q> Identify and summarize the key insights from the statistical analysis performed on the experimental results.
 I> 
 A> The statistical analysis shows that the proposed method significantly outperforms other methods in terms of both accuracy and runtime (p < 2.2e-16) for a majority of the communication scenarios. The gains in accuracy range between 1.5% and 13.4%.


 76% 76/100 [07:22<02:01,  5.05s/it]INFO 2024-06-26 22:07:17,856 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Identify the primary datasets used in the research and the corresponding data sources.
 I> Dataset 1: Sequence Read Archive (SRA), NCBI; Dataset 2: 1000 Genomes Project; Dataset 3: UK Biobank
 A> The primary datasets used in the research are Dataset 1, Dataset 2, and Dataset 3. Dataset 1 was obtained from the Sequence Read Archive (SRA) at NCBI, Dataset 2 was taken from the 1000 Genomes Project, and Dataset 3 was acquired from the UK Biobank.

 Q> What are the key utility measures used for evaluating the methods' performance?
 I> Accuracy, F1-score, Area Under the Precision-Recall Curve (AUPRC), and Area Under the ROC Curve (AUROC)
 A> The key utility measures used for evaluating the methods' performance are Accuracy, the F1-score, the Area Under the Precision-Recall Curve (AUPRC), and the Area Under the ROC Curve (AUROC).


 78% 78/100 [07:33<01:51,  5.06s/it]INFO 2024-06-26 22:07:28,012 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 INFO 2024-06-26 22:07:31,640 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Describe the primary research objective of the given paper.
 I> ## Unlocking Secrets of AI: A Comprehensive Review and Look into the Future

 This paper provides a comprehensive review of artificial intelligence (AI) research and technology, focusing on identifying the current trends and future prospects of this rapidly evolving field.
 A> The primary research objective of this paper is to review and analyze the current state of AI research and technology and forecast future trends in the field.

 Q> Compile the key contributions of the research.
 I> ## IoT-Based Wildlife Monitoring System with Adaptive and Reliable Communication

 The contributions of this paper are: (1) proposing a novel IoT-based wildlife monitoring system, (2) developing an adaptive and reliable communication algorithm, and (3) validating the system's performance using simulations and experiments.
 A> The study's key contributions are: (1) proposing a new IoT-based wildlife monitoring system, (2) creating an adaptive and reliable communication algorithm, and (3) validating the system's performance using simulations and experiments.


 80% 80/100 [07:46<01:52,  5.61s/it]INFO 2024-06-26 22:07:41,590 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Formulate the null and alternative hypotheses for the experimental comparisons made in the paper.
 I> 
 A> Null hypothesis (H0): The proposed method is not significantly different from other methods in terms of accuracy and runtime. Alternative hypothesis (H1): The proposed method is superior in accuracy or runtime to other methods or both.

 Q> Extract the relevant size and number of datasets used in the experimental evaluations presented in the paper.
 I> 
 A> Ten real-world and six synthetic datasets, with sizes ranging from 14MB to 1.1GB, were used in the experimental evaluations.


 82% 82/100 [07:55<01:35,  5.29s/it]INFO 2024-06-26 22:07:50,746 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> What is the main objective or goal of the research presented in the paper?
 I> 
 A> The main goal of the research is to design and develop a real-time, low-cost, and accurate object detection system using deep learning techniques.

 Q> List the key evaluations conducted to assess the performance of the proposed approach.
 I> ## Evaluations: Precision, Recall, and F1-Score

 The researchers evaluate the proposed approach using three main metrics: Precision, Recall, and F1-Score.
 A> The key evaluations conducted to assess the performance of the proposed approach include Precision, Recall, and F1-Score.


 84% 84/100 [08:04<01:21,  5.08s/it]INFO 2024-06-26 22:07:59,964 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Identify the authors and their affiliations from the given abstract.
 I> ## Discovering the Heterogeneity of Illegal Trading Communities via Geo-Social Detection: A Case Study of Suizhong County, China

 Tianyu Shi, Tianxing Wu, Ziming Zhao, Jiachen He, Yulong Pei, Xiangyu Jing, Zhijing Wang, Xiangfu Meng, Cheng Lu

 School of Data Science and Engineering, East China Normal University
 A> Tianyu Shi, Tianxing Wu, Ziming Zhao, Jiachen He, Yulong Pei, Xiangyu Jing, Zhijing Wang, Xiangfu Meng, and Cheng Lu from the School of Data Science and Engineering, East China Normal University are the authors of the presented research.

 Q> List the dataset(s) used in the study, and briefly summarize its significance in the context of the research.
 I> 
 A> Two datasets, DyD-2021 and DyD-Facebook, were used in this study. DyD-2021 is a dataset of drug trafficking online communities, and DyD-Facebook is a dataset of criminal groups active on Facebook. These datasets were instrumental for investigating the heterogeneity of illegal trading communities in online platforms.


 86% 86/100 [08:15<01:12,  5.18s/it]INFO 2024-06-26 22:08:10,783 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Extract the methodology or technical approach from the provided abstract.
 I> ## Method of detecting contractions in speech through real-time spectrogram processing and machine learning techniques

 In this study, we developed a novel method for detecting contractions in speech by combining real-time spectrogram processing and specialized machine learning techniques. We extracted Mel-frequency cepstral coefficients (MFCCs) from speech segments and fed them into an LSTM network for contraction detection.
 A> The methodology described in the abstract involves real-time spectrogram processing, Mel-frequency cepstral coefficients (MFCC) extraction, and a long short-term memory (LSTM) network.

 Q> In the dataset discussed, name the input and output variables detailed in the abstract.
 I> ## A Framework for Causality Attribution through Recursive Evolutionary Selection

 We propose a framework that can attribute causality to variables in complex datasets through recursive evolutionary feature selection and statistical tests. This approach effectively handles highly non-Gaussian collinear variables, evaluating each variable's causality in relation to the output variable of interest.
 A> The input variables are the complex dataset's features, which undergo recursive evolutionary feature selection, and the output variable of interest is the target for causality evaluation.


 88% 88/100 [08:26<01:02,  5.21s/it]INFO 2024-06-26 22:08:21,318 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Abstract the paper's contributions in a .csv format with two columns: "Contribution" and "Details."
 I> This paper aims at developing a lightweight text classification model (LightTxt) for edge computing scenarios. LightTxt consists of three modules - feature extraction, classification, and post-processing. These modules form a hierarchical architecture with the ability to perform piecemeal computation. The model has been benchmarked against several state-of-the-art models, demonstrating superior performance in three edge computing datasets.
 A> Contribution, Details
 Development of LightTxt, A lightweight text classification model designed for edge computing scenarios.
 Architecture, Three modules forming a hierarchical architecture capable of piecemeal computation.
 Performance, Demonstrated superior performance against state-of-the-art models on three edge computing datasets.

 Q> Present the methanol production costs (USD/Liter) of three different catalytic systems in a .csv format with the header row as "Catalyst" and "Cost."
 I> 
 A> Catalyst, Cost
 Catalyst X, USD 2.36
 Catalyst Y, USD 1.92
 Catalyst Z, USD 2.08


 90% 90/100 [08:36<00:52,  5.22s/it]INFO 2024-06-26 22:08:31,804 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Determine the number of authors in the paper.
 I> 
 A> The number of authors in the paper is five.

 Q> Identify any notable keywords relevant to the domain within the abstract.
 I> ## Exploring the Impact of Particular Layers for Training Deep Neural Networks

 In our study, we explored the impact of particular layers during training deep neural networks. We observed that early stop, batch normalization, and learned initialization play a crucial role in improving the generalization performance of a 12-layer deep neural network.
 A> Notable keywords relevant to the domain include layers, deep neural networks, early stop, batch normalization, learned initialization, and generalization performance.


 92% 92/100 [08:46<00:40,  5.05s/it]INFO 2024-06-26 22:08:41,140 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Identify the limitations of the study conducted in "A study of the performance of long short-term memory networks in text classification.
 I> 
 A> Limitation
 -Lack of a large and diverse dataset for text classification.
 -Dependence on pre-trained models which might not be optimal for specific text classification tasks.
 -Limited exploration of other deep learning architectures for text classification.


 93% 93/100 [08:52<00:36,  5.22s/it]INFO 2024-06-26 22:08:47,130 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> What are the key measures used in the paper to evaluate the data utility?
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab

 ## Abstract

 [...]

 ## 1 Introduction

 [...]
 A> The key measures used in the paper to evaluate the data utility are accuracy, recall, and F1-score for classification tasks, as well as signal-to-noise ratio for regression tasks.

 Q> Provide the dataset details used as the foundation for the research.
 I> 
 A> The paper uses the Adult Income and Credit Approval datasets from the UCI Repository, consisting of around 45K to 65K samples and 9 to 14 attributes, with a focus on evaluating data synthetic utility in classification and regression tasks.


 95% 95/100 [09:02<00:25,  5.13s/it]INFO 2024-06-26 22:08:57,048 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 INFO 2024-06-26 22:09:01,995 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> What are the key findings discussed in the technical paper's abstract?
 I> 
 A> The abstract presents a novel technique for identifying structural similarity between code snippets and algorithms. It introduces a representation learning model based on graph neural networks to generate structural embeddings. Using cosine distance for similarity measures, the proposed method demonstrates superior performance compared to traditional methods for similarity detection.

 Q> Identify the datasets used in the study mentioned in the given abstract.
 I> In order to develop the algorithm, we utilized datasets from UCI and Mozilla's Common Voice project.
 A> The UCI and Mozilla's Common Voice project datasets were employed in the study mentioned in the abstract.


 97% 97/100 [09:16<00:17,  5.76s/it]INFO 2024-06-26 22:09:11,204 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 INFO 2024-06-26 22:09:12,721 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> What assumptions were made in this research?
 I> 
 A> Assumptions
 The research assumed that the data obtained was representative and that it would not change over time. Also, it was assumed that there was a causal relationship between the dependent and independent variables.

 Q> What are the results of the experiment performed in the paper?
 I> ## Machine Learning Applications in Image Recognition

 The experiment performed in the paper showed that machine learning algorithms could achieve an accuracy of 95% on image recognition tasks.
 A> The results of the experiment performed in the paper showed that machine learning algorithms could achieve a high degree of accuracy on image recognition tasks. This establishes the potential of machine learning in the field of image recognition.


 99% 99/100 [09:27<00:05,  5.66s/it]INFO 2024-06-26 22:09:22,097 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->csv
 Q> Identify the dataset used in the paper and its associated task.
 I> ## Learning Disentangled and Transferable Representations for Private Data

 Jieyu Zhang, Hao Wang, Ce Zhang, Hsi-Yung Fan, Yifei Ma, Kristjan Greenewald, Akash Srivastava

 ## Abstract

 [...]

 ## 1 Introduction

 [...]
 A> The dataset used in the paper is the Adult Income dataset, and its associated task is income prediction.

 Q> What are the proposed methods for addressing data leakage in the paper?
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab

 ## Abstract

 [...]

 ## 1 Introduction

 [...]
 A> The proposed methods for addressing data leakage in the paper are DP-LSH, DP-wSGD, DP-Median, and DP-Adapted.


 101it [09:37,  5.51s/it]            
 101it [09:37,  5.72s/it]
 INFO 2024-06-26 22:09:32,469 generate_data.py:609: generate_data 101 instructions generated, 29 discarded due to format (see /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/technical_paper/abstract/csv/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_59_54.log), 1 discarded due to rouge score
 INFO 2024-06-26 22:09:32,469 generate_data.py:613: generate_data Generation took 577.56s
 Completed 87.4 KiB/202.0 KiB (536.6 KiB/s) with 4 file(s) remaining
 upload: ../outputtopush/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T21_59_54.json to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/technical_paper/abstract/csv/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T21_59_54.json
 Completed 87.4 KiB/202.0 KiB (536.6 KiB/s) with 3 file(s) remaining
 Completed 108.5 KiB/202.0 KiB (639.4 KiB/s) with 3 file(s) remaining
 upload: ../outputtopush/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_59_54.log to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/technical_paper/abstract/csv/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T21_59_54.log
 Completed 108.5 KiB/202.0 KiB (639.4 KiB/s) with 2 file(s) remaining
 Completed 190.9 KiB/202.0 KiB (1.0 MiB/s) with 2 file(s) remaining  
 upload: ../outputtopush/train_Mixtral-8x7B-Instruct-v0_2024-06-26T21_59_54.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/technical_paper/abstract/csv/train_Mixtral-8x7B-Instruct-v0_2024-06-26T21_59_54.jsonl
 Completed 190.9 KiB/202.0 KiB (1.0 MiB/s) with 1 file(s) remaining
 Completed 202.0 KiB/202.0 KiB (855.2 KiB/s) with 1 file(s) remaining
 upload: ../outputtopush/test_Mixtral-8x7B-Instruct-v0_2024-06-26T21_59_54.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/technical_paper/abstract/csv/test_Mixtral-8x7B-Instruct-v0_2024-06-26T21_59_54.jsonl
 compositional_skills/writing/freeform/prose/screenplay/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/writing/freeform/prose/screenplay/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/writing/freeform/prose/screenplay --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T22:09:34Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/writing/freeform/prose/screenplay/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 22:09:43,183 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->writing->freeform->prose->screenplay
 [31mGenerating dataset failed with the following error: There was a problem with the new data, please make sure the yaml is formatted correctly, and there is enough new data(2+ Q&A))[0m

  0% 0/100 [00:00<?, ?it/s]
 compositional_skills/extraction/services_agreement/plain_text/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/extraction/services_agreement/plain_text/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/services_agreement/plain_text --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T22:09:44Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/extraction/services_agreement/plain_text/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 22:09:52,412 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text

  0% 0/100 [00:05<?, ?it/s]INFO 2024-06-26 22:09:57,519 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What is the maximum duration of this Agreement?
 I> The term of this Agreement shall be from \_\_\_\_\_ to \_\_\_\_\_. The Agreement may be terminated earlier by final completion of the Services by the Consultant and acceptance of the services by the County or through the termination provisions provided herein.
 A> The maximum duration of this Agreement is not explicitly stated. However, it can be from the time specified in the first blank to the time specified in the second blank.


  1% 1/100 [00:10<09:23,  5.69s/it]INFO 2024-06-26 22:10:03,214 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What is the total fee that the Consultant is going to receive for this project?
 I> 6. Payment. The County shall pay Consultant for the Services specified as follows:

 A. Hourly Charges. Consultant shall be compensated at the rate of $70.00 per hour for the services of the Consultant and his/her employees.

 B. Expenses. Consultant may be reimbursed for the reasonable expenses incurred by Consultant in performing the services upon presentation of valid receipts for such expenditures.

 C. Mileage. Consultant shall be reimbursed for all travel at the current rate as established by law.

 D. Payment. Payment for all amounts due under this Section shall be due to Consultant within thirty (30) days of receipt of each invoice submitted by Consultant.
 A> The Consultant is going to receive $70.00 per hour for the services of the Consultant and his/her employees.

 Q> What are the conditions for the County to terminate this Agreement?
 I> 4. Termination. Consultant may terminate this Agreement at any time by giving the County written notice of not less than sixty (60) days. County may terminate this Agreement at any time in the event that Consultant violates the terms of this Agreement or fails to produce a result that meets the specifications of this Agreement. In the event of termination, payments will be made to Consultant for all work performed up to the date of termination.
 A> The County may terminate this Agreement at any time in the event that Consultant violates the terms of this Agreement or fails to produce a result that meets the specifications of this Agreement.


  3% 3/100 [00:22<09:16,  5.74s/it]INFO 2024-06-26 22:10:14,717 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Identify the time frame for payments to be made after the receipt of an invoice.
 I> Payment of such invoices will be due within twenty-five (25) days of the receipt thereof.
 A> Payments will be due within 25 days of the receipt of an invoice.

 Q> What is the policy regarding Consultant's entitlement to County employment benefits?
 I> 5. Relationship. The parties understand and agree that Consultant is an independent Consultant and that Consultant is not an employee, agent or servant of the County, nor is Consultant entitled to County employment benefits.
 A> Consultant is not entitled to County employment benefits.


  5% 5/100 [00:31<08:14,  5.20s/it]INFO 2024-06-26 22:10:24,121 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What is the format and deadline for the Consultant to submit their invoice?
 I> 13. Invoicing. Consultant shall submit an original invoice in a format acceptable to the County's Financial Services Division on a monthly basis for work performed during the previous month. Invoices shall be submitted no later than the 15th of the month following the performance of work.
 A> You need to submit an original invoice in an acceptable format to the County's Financial Services Division on a monthly basis by the 15th of the following month.

 Q> As a County employee, I need to know the effective date of the consultant agreement.
 I> 1. Agreement. This Agreement is made and entered into this day of , 20.
 A> The effective date of the consultant agreement is the day of , 20.


  7% 7/100 [00:41<07:48,  5.04s/it]INFO 2024-06-26 22:10:33,759 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What is the time frame of the agreement between the Consultant and the County?
 I> 
 A> The time frame of the agreement is from the start date to the end date specified in the Agreement. The Agreement may also be terminated earlier if the Services are completed or if the Agreement is terminated due to a violation of its terms.

 Q> Who is responsible for the proper performance of the Services, the Consultant or the County?
 I> E. All Services are to be performed solely at the risk of the Consultant and Consultant shall take all precautions necessary for the proper performance thereof; and
 A> The Consultant is responsible for the proper performance of the Services.


  9% 9/100 [00:50<07:25,  4.90s/it]INFO 2024-06-26 22:10:43,083 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Who is responsible for obtaining and maintaining insurance as per the agreement?
 I> 6. Insurance. Consultant will obtain and maintain at its expense any required permits, licenses, bonding, insurance and any other necessary authorizations or approvals required for the performance of the tasks to be undertaken by Consultant.
 A> Consultant is responsible for obtaining and maintaining at its expense any required insurance as per the agreement.

 Q> When is the Consultant required to provide certificates of insurance to the County?
 I> 8. Indemnification and Insurance. Consultant shall indemnify and hold harmless the County from and against all claims, damages, losses, and expenses arising out of or resulting from acts or omissions of the Consultant, Consultant's sub-Consultants or otherwise arising out of the performance of services by Consultant. No later than seven days after execution of this Agreement, Consultant shall provide the County with certificates of insurance evidencing the types and amounts of insurance specified below:
 A> The Consultant is required to provide certificates of insurance to the County no later than seven days after execution of this Agreement.


 11% 11/100 [01:00<07:22,  4.97s/it]INFO 2024-06-26 22:10:53,292 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Summarize the consequences for not obtaining insurance coverage as specified in the agreement.
 I> Failure to obtain insurance coverage, or cancellation or termination of insurance coverage without the County's written approval, shall constitute a material breach of the Agreement and shall automatically terminate the Agreement.
 A> Not obtaining insurance coverage or cancelling or terminating it without the County's written approval will result in a material breach of the agreement and automatic termination of the agreement.

 Q> Determine the limit of liability for personal injury and property damage in the General Liability Insurance.
 I> Comprehensive General Liability Insurance for operations and contractual liability with limits of not less than $350,000 on account of any one person and $990,000 for each occurrence of property damage and personal injury.
 A> The limit of liability for personal injury is $350,000 on account of any one person, and $990,000 for each occurrence of property damage and personal injury.


 13% 13/100 [01:10<07:13,  4.98s/it]INFO 2024-06-26 22:11:03,311 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Specify who is responsible for providing the deliverables in the 2nd paragraph of the Given Agreement.
 I> 2. Deliverables. Consultant shall deliver to the County such deliverables as are described in **Exhibit B** and of the quality described therein on the dates specified therein. The deliverables shall become the property of the County upon delivery and acceptance by County.
 A> The Consultant is responsible for providing the deliverables as described in Exhibit B and of the quality described therein on the dates specified.

 Q> What is the date by which the Consultant should deliver the first deliverable mentioned in Exhibit B according to the Given Agreement?
 I> 
 A> The specific date by which the Consultant should deliver the first deliverable mentioned in Exhibit B is not provided in the agreement.


 15% 15/100 [01:20<06:58,  4.92s/it]INFO 2024-06-26 22:11:12,876 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What is the specific date for the completion of the project regarding the cost estimate?
 I> 10. Performance. Consultant shall complete performance under this contract by the following dates:

 a. Cost Estimate: March 31, 2022

 b. Additional Tasks: As specified in the attached Work Order
 A> The cost estimate shall be completed by March 31, 2022.

 Q> Who is responsible for the setup and installation of the software, as indicated in the agreement?
 I> 14. Software. The County shall provide access to all necessary software for completing the scope of services outlined in this contract. The software shall be installed by the County's IT department.
 A> The County's IT department is responsible for the setup and installation of the software.


 17% 17/100 [01:29<06:44,  4.87s/it]INFO 2024-06-26 22:11:22,409 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Can you identify the section of the agreement that defines the payment schedule for the Consultant?
 I> 
 A> The payment schedule for the Consultant is defined in Section 6 of the agreement.

 Q> What are the terms of reimbursement for expenses incurred by the Consultant?
 I> 6. Payment. The County shall pay Consultant for the Services specified as follows:

 A. Hourly Charges. Consultant shall be compensated at the rate of $70.00 per hour for the services of the Consultant and his/her employees.

 B. Expenses. Consultant may be reimbursed for the reasonable expenses incurred by Consultant in performing the services upon presentation of valid receipts for such expenditures.

 C. Mileage. Consultant shall be reimbursed for all travel at the current rate as established by law.

 D. Payment. Payment for all amounts due under this Section shall be due to Consultant within thirty (30) days of receipt of each invoice submitted by Consultant.
 A> The Consultant may be reimbursed for the reasonable expenses incurred in performing the services upon presentation of valid receipts for such expenditures.


 19% 19/100 [01:40<06:42,  4.97s/it]INFO 2024-06-26 22:11:32,760 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 INFO 2024-06-26 22:11:34,599 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Which services are the Consultant responsible for delivering?
 I> 1. Scope of Services. The Consultant will perform the following services for the County: a. Preparation of a detailed project plan and schedule for the project; b. Development of the User Guide documentation; c. Development of an implementation plan; d. Configuration and testing of the software system; e. Installation of the software system; f. Training of County staff on the use of the software system; g. Consultation services for the County staff and post-installation support.
 A> The Consultant is responsible for delivering the following services: preparation of a detailed project plan and schedule, development of a user guide documentation, development of an implementation plan, configuration and testing of the software system, installation of the software system, training of County staff on the use of the software system, consultation services for the County staff, and post-installation support.

 Q> What is the Consultant's hourly rate for this project?
 I> 5. Payment. The Consultant shall be paid an hourly rate of $150 for services rendered and for any reimbursable expenses.
 A> The Consultant's hourly rate for this project is $150.


 21% 21/100 [01:52<06:59,  5.32s/it]INFO 2024-06-26 22:11:44,974 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What are the specific deadlines for the deliverables mentioned in the email agreement?
 I> 7. Deliverables. Consultant shall deliver the following to the County:
 A. A final report including statistical analysis and recommendations for implementation; due 60 days from the effective date.
 B. Two training sessions with County staff on data analysis and report interpretation; first session due 45 days from the effective date, and the second session due 15 days after the first session.
 A> The specific deadlines for the deliverables mentioned in the email agreement are:
 - A final report including statistical analysis and recommendations for implementation: due 60 days from the effective date.
 - The first training session with County staff on data analysis and report interpretation: due 45 days from the effective date.
 - The second training session with County staff on data analysis and report interpretation: due 15 days after the first session.

 Q> What mentioned methods will be used by the provider for collecting the data?
 I> 5. Data Collection. The provider shall use the following methods for data collection:
 A. Surveys
 B. Interviews
 C. Publicly available data
 A> The provider mentioned using surveys, interviews, and publicly available data for collecting the data.


 23% 23/100 [02:03<06:48,  5.31s/it]INFO 2024-06-26 22:11:55,538 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Identify what the County will own once the deliverables have been accepted.
 I> 2. **Deliverables.** Consultant shall deliver to the County such deliverables as are described in Exhibit B and of the quality described therein on the dates specified therein. The deliverables shall become the property of the County upon delivery and acceptance by County.
 A> The County will own the deliverables once they have been delivered and accepted by the County.


 24% 24/100 [02:09<06:52,  5.43s/it]INFO 2024-06-26 22:12:01,520 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 INFO 2024-06-26 22:12:04,422 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Identify the conditions under which the County may terminate the agreement.
 I> 4. Termination. County may terminate this Agreement at any time in the event that Consultant violates the terms of this Agreement or fails to produce a result that meets the specifications of this Agreement. In the event of termination, payments will be made to Consultant for all work performed up to the date of termination.

 A. Fund Availability/Annual Appropriation. Payment pursuant to this Agreement, whether in whole or in part, is subject to and contingent upon the continuing availability of County funds for purposes hereof. In the event that said funds, or any part thereof, become unavailable as determined by the County, the County may immediately terminate this Agreement or amend it accordingly.

 B. Suspension of Services. Should the County determine that suspension of all or any portion of the Services is necessary for reasons of public safety or health, the County shall have the right to immediately suspend such Services in whole or in part upon written notice to Consultant. Consultant shall immediately cease providing such suspended Services and shall not resume providing suspended Services until written notice is received from the County authorizing such resumption.
 A> The County may terminate the agreement if the Consultant violates the terms of the agreement or fails to produce a result that meets the specifications of the agreement. The County may also terminate the agreement if County funds for the agreement become unavailable or if suspension of services is necessary for reasons of public safety or health.

 Q> What is the payment schedule for invoices submitted by the consultant?
 I> <noinput>

 1. Invoices. Requisitions and invoices for services rendered and supplies and materials furnished under this Agreement shall be submitted by Consultant to the County at such times and in such manner as may be mutually agreed upon by the Parties. Invoices shall be submitted no later than thirty (30) days following the end of each calendar month during the Term.

 2. Payment. Payment of all undisputed amounts stated in invoices duly submitted hereunder shall be made by the County to Consultant within thirty (30) days after receipt by the County of the invoices.
 A> Invoices submitted by the consultant should be submitted at times and in a manner mutually agreed upon by the parties, no later than 30 days following the end of each calendar month during the term. Payment of all undisputed amounts stated in the invoices should be made by the County to the Consultant within 30 days after receipt by the County of the invoices.


 26% 26/100 [02:25<07:48,  6.33s/it]INFO 2024-06-26 22:12:17,712 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What are the reporting requirements for the Consultant?
 I> C. Reports. Consultant shall submit reports to the County as follows:
 i. One (1) week prior to the start of the Services, Consultant shall submit a proposed plan for providing the Services and any available data to support the proposed plan.
 ii. Upon completion of the Services, Consultant shall submit a final report detailing the results of the Services, in a format specified by the County.
 A> The Consultant is required to submit a proposed plan for providing the services one week prior to the start of the services and a final report detailing the results of the services upon completion of the services.

 Q> What is the time frame for the Services to be performed?
 I> B. Schedule. The Services shall be performed within ninety (90) days of the Effective Date.
 A> The Services must be performed within ninety (90) days of the Effective Date.


 28% 28/100 [02:34<07:00,  5.84s/it]INFO 2024-06-26 22:12:27,388 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 INFO 2024-06-26 22:12:29,984 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What are the services that the Consultant shall render to the County?
 I> 1. Scope of Services. The Consultant shall perform professional consulting services as described in Exhibit A attached hereto as if it were set forth fully herein.
 A> The Consultant shall render professional consulting services as described in Exhibit A of this Agreement.

 Q> What are the requirements for the Consultant's payment?
 I> 6. Compensation. The County will pay the Consultant for services rendered as stated herein in accordance with the County's standard procedures and policies and the Consultant agrees to comply with any and all invoicing, payment, expense and other requirements in connection with this Agreement.
 A> The Consultant's payment will be made in accordance with the County's standard procedures and policies, and the Consultant agrees to comply with any invoicing, payment, and expense requirements.


 30% 30/100 [02:47<06:56,  5.95s/it]INFO 2024-06-26 22:12:39,719 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What is the required format for the User Guide documentation?
 I> 2. Scope of Services. The Consultant will perform the following services for the County: b. Development of the User Guide documentation.
 3. Deliverables. The deliverables under this Agreement will be: a. User Guide documentation, which will be in the form of a detailed user manual in Adobe PDF format, containing step-by-step instructions for the use of the software system.
 A> The User Guide documentation should be in the form of a detailed user manual in Adobe PDF format, containing step-by-step instructions for the use of the software system.

 Q> What kind of post-installation support is covered in this agreement?
 I> 1. Scope of Services. The Consultant will perform the following services for the County: g. Consultation services for the County staff and post-installation support.
 7. Post-Installation Support. The Consultant will provide post-installation support to the County, including troubleshooting, bug fixing, and phone or email support for a period of ninety (90) days following the installation of the software system.
 A> The Consultant will provide post-installation support to the County for a period of ninety (90) days following the installation of the software system, which includes troubleshooting, bug fixing, and phone or email support.


 32% 32/100 [02:57<06:30,  5.74s/it]INFO 2024-06-26 22:12:50,285 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 INFO 2024-06-26 22:12:52,548 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 INFO 2024-06-26 22:12:54,564 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What are the specifications for the termination of the Consultant in the agreement?
 I> 4. Termination. Consultant may terminate this Agreement at any time by giving the County written notice of not less than sixty (60) days. County may terminate this Agreement at any time in the event that Consultant violates the terms of this Agreement or fails to produce a result that meets the specifications of this Agreement. In the event of termination, payments will be made to Consultant for all work performed up to the date of termination.
 A> If the Consultant wishes to terminate the agreement, they must provide written notice to the County at least 60 days in advance. The County can terminate the agreement immediately if the Consultant violates the terms or fails to meet the specifications of the agreement.

 Q> What are the obligations of the County in the agreement?
 I> C. Multi-Year Contracts. The obligations of the County hereunder shall not constitute a general obligation indebtedness or multiple year direct or indirect debt or other financial obligation whatsoever within the meaning of the Constitution or laws of the State of Colorado.

 3. Term. The term of this Agreement shall be from ____________ to _____________. The Agreement may be terminated earlier by final completion of the Services by the Consultant and acceptance of the services by the County or through the termination provisions provided herein.

 5. Relationship. The parties understand and agree that Consultant is an independent Contractor and that Consultant is not an employee, agent or servant of the County, nor is Consultant entitled to County employment benefits. CONSULTANT UNDERSTANDS AND AGREES THAT CONSULTANT IS NOT ENTITLED TO WORKERS' COMPENSATION BENEFITS AND THAT CONSULTANT IS OBLIGATED TO PAY FEDERAL AND STATE INCOME TAX ON ANY MONEYS EARNED PURSUANT TO THIS CONTRACT. As an independent Contractor, Consultants agrees that:
 A> The obligations of the County in the agreement include not treating the contract as a general obligation indebtedness or financial obligation. The County's obligations begin on the start date of the agreement and can end early if the services are completed and accepted or through the termination provisions. The County also agrees that the Consultant is an independent contractor and not an employee, entitled to any employment benefits, and responsible for paying their own income taxes.


 34% 34/100 [03:15<07:18,  6.64s/it]INFO 2024-06-26 22:13:07,630 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Can you summarize the payment terms for the Consultant's invoices in this agreement?
 I> 13. Invoicing. Consultant shall submit an original invoice in a format acceptable to the County's Financial Services Division on a monthly basis for work performed during the previous month. Invoices shall be submitted no later than the 15th of the month following the performance of work. Payment of such invoices will be due within twenty-five (25) days of the receipt thereof.
 A> The Consultant should submit an original invoice in an acceptable format on a monthly basis within 15 days of the previous month's work. The County will pay the invoice within 25 days of receipt.

 Q> What is the time duration of this agreement?
 I> 3. Term. The term of this Agreement shall be from ____________ to _____________. The Agreement may be terminated earlier by final completion of the Services by the Consultant and acceptance of the services by the County or through the termination provisions provided herein.
 A> The time duration of the agreement is from a specific start date to a specific end date.


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 INFO 2024-06-26 22:13:21,130 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What are the responsibilities of the Service Provider during the warranty period?
 I> The Service Provider is responsible for providing maintenance services during the warranty period for all services performed under this Agreement. This includes any necessary repairs or replacements to remedy any defects in the Services.
 A> The Service Provider is responsible for providing maintenance services and remedying any defects in the Services through necessary repairs or replacements during the warranty period.

 Q> What is the charge for the Additional Services requested by the Client?
 I> $100 per hour for Additional Services, billed in half-hour increments.
 A> The charge for Additional Services is $100 per hour, billed in half-hour increments.


 38% 38/100 [03:37<06:24,  6.21s/it]INFO 2024-06-26 22:13:30,413 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What is the duration of the agreement between the County and the Consultant?
 I> This Agreement made and entered into this ______ day of _______________, 20_____, by and between Ada County, herein referred to as "County," and ________________, herein referred to as "Consultant," and any change to this Agreement must be in writing and signed by both parties.

 1. Statement of Work. For all Statements of Work, the Consultant shall provide all labor, materials, tools and equipment necessary for the timely and proper performance of the Services. Consultant has the sole and exclusive right to control and direct the means, details and methods of performing the Services. The County shall have no right to control or direct Consultant's performance of the Services.

 2. Term. The term of this Agreement shall be from ____________ to _____________.

 3. Termination. Consultant may terminate this Agreement at any time by giving the County written notice of not less than sixty (60) days. County may terminate this Agreement at any time in the event that Consultant violates the terms of this Agreement or fails to produce a result that meets the specifications of this Agreement. In the event of termination, payments will be made to Consultant for all work performed up to the date of termination.

 5. Relationship. The parties understand and agree that Consultant is an independent Contractor and that Consultant is not an employee, agent or servant of the County, nor is Consultant entitled to County employment benefits. CONSULTANT UNDERSTANDS AND AGREES THAT CONSULTANT IS NOT ENTITLED TO WORKERS' COMPENSATION BENEFITS AND THAT CONSULTANT IS OBLIGATED TO PAY FEDERAL AND STATE INCOME TAX ON ANY MONEYS EARNED PURSUANT TO THIS CONTRACT.
 A> The duration of the agreement between the County and the Consultant is from the start date to the end date filled in the agreement.


 39% 39/100 [03:46<06:41,  6.58s/it]INFO 2024-06-26 22:13:38,686 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What is the requirement for adding new users to the system?
 I> Adding new users will require a written request from an officer of the Company to the Support Team and the provision of the necessary identification information required for the creation of their account.
 A> Adding new users to the system requires a written request from an officer of the Company and the provision of necessary identification information.

 Q> What is the process for reporting and addressing errors or issues in the software?
 I> To report errors or issues, users should contact the Support Team through the designated email address and provide as much detail as possible, including the steps taken, the expected and actual outcomes, and any error messages. The Support Team will acknowledge receipt of the error report and provide timely updates on the progress of the resolution.
 A> To report errors or issues, users should contact the Support Team with as much detail as possible, including steps taken and expected and actual outcomes. The Support Team will provide timely updates on the progress of the resolution.


 41% 41/100 [03:56<05:55,  6.03s/it]INFO 2024-06-26 22:13:48,593 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What are the terms and conditions related to the protection of intellectual property?
 I> 18. Ownership of Deliverables. Consultant agrees that all deliverables developed under this agreement shall be the exclusive property of the County. Consultant shall not distribute or make use of any deliverables without the express written permission of the County.
 A> The Consultant agrees that they will not distribute or make use of any deliverables without the County's express written permission, and that all deliverables developed under this agreement will be the County's exclusive property.

 Q> What constitutes a breach of the confidentiality clause under this agreement?
 I> 21. Confidentiality. Consultant shall not at any time, whether during the term of this agreement or thereafter, use, disclose, or make available to any other person or entity any confidential information or proprietary data belonging to the County.
 A> A breach of the confidentiality clause under this agreement would occur if the Consultant uses, discloses, or makes available any confidential information or proprietary data belonging to the County to any other person or entity.


 43% 43/100 [04:06<05:25,  5.71s/it]INFO 2024-06-26 22:13:58,706 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What happens to any unpaid fees if either party terminates the agreement early?
 I> 12. **Termination of Agreement.** Either party may terminate this Agreement upon providing thirty (30) days written notice to the other party of its intent to terminate the Agreement. Upon termination of this Agreement, Consultant shall be compensated for Services performed up to the date of termination; provided, however, that in the event of Consultant's default, the County shall not be obligated to make any further payments.
 A> If either party terminates the agreement early, the Consultant will be compensated for Services performed up to the date of termination. However, if the Consultant is in default, the County has no obligation to make any further payments.

 Q> What kind of confidential information is prohibited from disclosing by the Consultant?
 I> 4. **Confidential Information.** The term "Confidential Information" shall mean any and all business, technical or financial information disclosed by either party before or after the execution of this Agreement. Any party receiving Confidential Information shall not disclose the same to third parties, except as required by law or by the order of a court or other governmental authority.
 A> The Consultant is prohibited from disclosing any business, technical, or financial information disclosed by either party before or after the execution of the agreement, except as required by law or by the order of a court or other governmental authority.


 45% 45/100 [04:17<05:08,  5.60s/it]INFO 2024-06-26 22:14:09,440 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 INFO 2024-06-26 22:14:11,762 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 INFO 2024-06-26 22:14:18,826 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Identify the two deliverables that the Consultant must provide to the County upon completion of the project.
 I> 15. Project Completion and Deliverables. Upon completion of the project, Consultant shall deliver the following to the County: a. Complete user guide documentation; b. Fully-functioning software system; c. Certification letter confirming completion of the project; d. 30-day guarantee and maintenance plan; e. Any material, equipment or software that was provided to Consultant by the County and that is still in Consultant’s possession or control.
 A> The two deliverables that the Consultant must provide to the County upon completion of the project are complete user guide documentation and a fully-functioning software system.

 Q> What is the timeframe for the Consultant to complete the software installation and training of County staff?
 I> 3. Software Implementation Plan. Consultant will develop a detailed software implementation plan that includes the following: a. Software installation schedule that identifies the installation date(s) and the time frame required for installation; b. Training schedule for County staff that identifies the training date(s) and the time frame required for training.
 A> The timeframe for the Consultant to complete the software installation and training of County staff is identified in the software implementation plan, which includes the installation schedule and training schedule to be developed by the Consultant.


 47% 47/100 [04:36<06:09,  6.96s/it]INFO 2024-06-26 22:14:29,366 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Has the Consultant provided a detailed breakdown of their hourly charges for services rendered in the past month?
 I> 5. Invoices. Consultant shall submit invoices for services rendered under this Agreement on a monthly basis to the County's Director of Finance or designee.

 6. Payment. The County shall pay Consultant for the Services specified as follows:

 A. Hourly Charges. Consultant shall be compensated at the rate of $70.00 per hour for the services of the Consultant and his/her employees.

 B. Expenses. Consultant may be reimbursed for the reasonable expenses incurred by Consultant in performing the services upon presentation of valid receipts for such expenditures.

 C. Mileage. Consultant shall be reimbursed for all travel at the current rate as established by law.

 D. Payment. Payment for all amounts due under this Section shall be due to Consultant within thirty (30) days of receipt of each invoice submitted by Consultant.
 A> According to the given agreement, the Consultant is required to submit invoices for services rendered under this Agreement on a monthly basis. However, the given text does not provide a detailed breakdown of the Consultant's hourly charges for services rendered in the past month.

 Q> Who has the authority to approve the Consultant's invoices before payment can be made?
 I> 
 A> According to the agreement, the County's Director of Finance or designee has the authority to approve the Consultant's invoices before payment can be made.


 49% 49/100 [04:48<05:34,  6.56s/it]INFO 2024-06-26 22:14:40,695 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Can you find out which party is responsible for payment of any taxes or fees incurred in the email agreement?
 I> 17. Taxes and Fees. Except as provided in this Agreement, all taxes (state and federal, including sales taxes), licenses, levies, imports, duties, fees and other charges now in force or enacted in the future (collectively, "Taxes") resulting from the provision of services by the Consultant shall be the responsibility of the Consultant.
 A> In the email agreement, the Consultant is responsible for payment of any taxes or fees incurred.

 Q> What are the exact services to be provided by the Consultant as per the agreement?
 I> 2. Services. Subject to the terms of this Agreement, Consultant shall provide the following services to the County (the "Services"):
 A. Statistical data analysis and interpretation;
 B. Training on statistical data analysis and report interpretation;
 C. Recommendations for policy and program implementation;
 A> According to the agreement, the Consultant shall provide the following services: statistical data analysis and interpretation, training on statistical data analysis and report interpretation, and recommendations for policy and program implementation.


 51% 51/100 [04:58<04:59,  6.11s/it]INFO 2024-06-26 22:14:50,893 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What is the timeline for the completion of the software development?
 I> 1. **Scope of Services.** The Consultant will perform the following services for the County: a. Software Development. The Consultant shall develop a software system to manage and track requests for services as described in Exhibit B. The software shall be developed in accordance with industry standard software development practices.
 2. **Deliverables.** The deliverables under this Agreement will be: a. The software system, which shall be delivered to the County on or before December 31, 2023.
 A> The software system is to be delivered to the County on or before December 31, 2023.

 Q> Which software development methodology is to be used?
 I> 1. **Scope of Services.** The Consultant will perform the following services for the County: a. Software Development. The Consultant shall develop a software system to manage and track requests for services as described in Exhibit B. The software shall be developed in accordance with industry standard software development practices.
 A> The software system is to be developed in accordance with industry standard software development practices.


 53% 53/100 [05:08<04:32,  5.81s/it]INFO 2024-06-26 22:15:01,089 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 INFO 2024-06-26 22:15:03,627 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What are the specific responsibilities of the Consultant, as outlined in this agreement?
 I> 4. Consultant's Responsibilities. The Consultant shall, at a minimum, be responsible for the following: (a) Performing all work related to the Services to be provided hereunder in a professional and workmanlike manner in accordance with generally recognized professional standards. (b) Preparing all necessary plans, drawings, specifications, surveys, and estimates. (c) Assisting the County in negotiating and obtaining contracts, leases, permits, licenses, and other necessary agreements. (d) Providing all necessary administrative and technical support, equipment, and personnel to properly perform the Services. (e) Consulting with, and obtaining the approval of, the County's designated representatives before making any changes to the plans, drawings, specifications, surveys, and estimates. (f) Performing all work in accordance with all applicable laws, regulations, and codes.
 A> The Consultant's specific responsibilities under this agreement include: performing all work related to the Services professionally, preparing necessary plans, drawings, specifications, surveys, and estimates, assisting the County in obtaining contracts, providing administrative and technical support, consulting with the County's representatives before making any changes, and performing all work in accordance with applicable laws.

 Q> Who is responsible for obtaining necessary contracts, leases, permits, licenses, and other necessary agreements in this agreement?
 I> 
 A> The Consultant is responsible for assisting the County in negotiating and obtaining contracts, leases, permits, licenses, and other necessary agreements.


 55% 55/100 [05:22<04:35,  6.12s/it]INFO 2024-06-26 22:15:14,805 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What are the specific terms of the County's payment obligations, as outlined in the agreement?
 I> 17. Payment. The County shall pay the Consultant for all services rendered pursuant to this agreement. The County shall remit payment to the Consultant on a monthly basis, within thirty (30) days after receiving an invoice.
 A> The County's payment obligations include remitting payment to the Consultant on a monthly basis, within thirty (30) days after receiving an invoice.

 Q> Who is responsible for ensuring compliance with all applicable laws, regulations, and ordinances during the performance of the services outlined in the agreement?
 I> 20. Legal Compliance. The Consultant shall perform all services under this agreement in compliance with all applicable laws, regulations, and ordinances.
 A> The Consultant is responsible for ensuring compliance with all applicable laws, regulations, and ordinances during the performance of the services outlined in the agreement.


 57% 57/100 [05:32<04:07,  5.76s/it]INFO 2024-06-26 22:15:24,639 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 INFO 2024-06-26 22:15:26,335 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What are the specifications of the report to be delivered by the Consultant?
 I> 5. Deliverables. Consultant shall provide the following deliverables: (i) a written report ("Report") that summarizes the results of the Research and provides a list of recommended actions for the County to take to address the identified issues, (ii) a presentation ("Presentation") that provides an overview of the Report and the recommended actions, and (iii) any other materials specified in the Scope of Work section of this Agreement.
 A> The deliverables specified in the email agreement include a written report summarizing the results of the research and providing a list of recommended actions, a presentation overviewing the report and recommendations, and any other materials specified in the Scope of Work section.

 Q> Who is the Consultant responsible for providing services and meeting the specifications in this Agreement?
 I> 2. Services. The Consultant shall provide the services ("Services") identified in the Scope of Work section of this Agreement ("Services"), which may be modified from time to time by the County in writing.
 A> The Consultant identified in the email agreement is responsible for providing the services specified in the Scope of Work section of the Agreement.


 59% 59/100 [05:44<03:59,  5.84s/it]INFO 2024-06-26 22:15:36,709 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What is the goal of the County's Technical Assistance Program?
 I> Tech Assistance Program. The County hereby establishes a Technical Assistance Program (the “Program”) designed to aid companies, institutions, and governmental entities (the “Participants”) in obtaining broad-based, knowledgeable information and technical assistance regarding renewable energy systems and technology. The Program shall be administered by the County with the assistance of its consultants and contractors.
 A> The goal of the County's Technical Assistance Program is to aid companies, institutions, and governmental entities in obtaining broad-based, knowledgeable information and technical assistance regarding renewable energy systems and technology through the assistance of the County's consultants and contractors.

 Q> What is the role of the County in the implementation of the software system?
 I> The County will have a Project Manager who will work closely with the Consultant during the software implementation process. The County Project Manager will be the primary liaison between the County and the Consultant. The County will be responsible for the following tasks: a) coordinating the approval of the software system configuration by the County departments; b) coordinating the installation of the software system; c) coordinating acceptance testing of the software system; and d) approving system go-live.
 A> The County's role in the implementation of the software system includes having a Project Manager who will work closely with the Consultant, coordinating the approval of the software system configuration, coordinating the installation of the software system, coordinating acceptance testing of the software system, and approving system go-live.


 61% 61/100 [05:55<03:44,  5.75s/it]INFO 2024-06-26 22:15:47,796 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 INFO 2024-06-26 22:15:52,333 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 INFO 2024-06-26 22:15:55,319 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What are the timelines that the Consultant is expected to follow in rendering the services?
 I> 2. Schedule. The Consultant shall render its Services on the dates listed in Exhibit B attached hereto as if it were set forth fully herein.
 A> The Consultant is expected to render services on the dates listed in Exhibit B.

 Q> What are the fees and reimbursable expenses payable to the Consultant for rendering the services?
 I> 3. Compensation. The County shall pay the Consultant a fixed fee of Five Hundred Thousand Dollars ($500,000) for rendering the Services under this Agreement. The County shall also reimburse the Consultant for all reasonable and necessary out-of-pocket expenses incurred by the Consultant in rendering the Services under this Agreement.
 A> The Consultant shall be paid a fixed fee of Five Hundred Thousand Dollars ($500,000) and be reimbursed for all reasonable and necessary out-of-pocket expenses incurred in rendering the services.


 63% 63/100 [06:12<04:06,  6.67s/it]INFO 2024-06-26 22:16:05,389 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Extract the description of the service and the corresponding charge from the provided email text.
 I> Thanks for your interest in our services! We have reviewed your request for consulting and are pleased to offer our professional services on a time and materials basis. Our consultant will assist you with reviewing and upgrading your existing network infrastructure and estimating the time required is three months. The standard hourly rate for this project is $165.
 A> The description of the service is the consultant will assist with reviewing and upgrading the existing network infrastructure, and the corresponding charge is $165 per hour.

 Q> Determine the two primary skills that the applicant must possess for the given job position.
 I> We are seeking a Junior Software Developer with the following qualifications: 

 1. At least 2 years of experience with Object-Oriented Programming (OOP) languages, such as C++, Java, or Python; 
 2. Excellent communication skills, both written and verbal; 
 3. Strong problem-solving skills and ability to work independently; 
 4. Experience using version control software, such as Git; 
 5. Familiarity with Agile and Scrum development methodologies; and 
 6. A bachelor's degree in Computer Science, Information Technology, or a related field.
 A> The two primary skills that the applicant must possess for the Junior Software Developer position are at least 2 years of experience with Object-Oriented Programming (OOP) languages and excellent communication skills, both written and verbal.


 65% 65/100 [06:24<03:42,  6.36s/it]INFO 2024-06-26 22:16:16,687 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 INFO 2024-06-26 22:16:20,228 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What is the deadline for the submission of the final report?
 I> 3. Deliverables. The Contractor shall submit a final report detailing all activities carried out under this Agreement no later than thirty (30) days after the completion of the Services.
 A> The deadline for the submission of the final report is thirty (30) days after the completion of the Services.

 Q> What information should be included in the incident report?
 I> 1. Incident Reporting. In the event of any incident, the Contractor shall promptly notify the Company in writing, setting forth all circumstances relating to the incident.
 A> An incident report should include all circumstances relating to the incident, including a detailed description of what happened.


 67% 67/100 [06:37<03:30,  6.38s/it]INFO 2024-06-26 22:16:29,530 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What is the procedure for addressing issues or disputes that arise in the agreement?
 I> 11. Issues or Disputes. Any issue, dispute, or controversy arising out of or relating to this Agreement, including the validity, interpretation, performance, or breach thereof, shall be resolved in accordance with Section 11.
 A> Any issues or disputes arising out of or relating to the agreement should be resolved in accordance with Section 11.

 Q> Who is the primary contact at the County for the Consultant?
 I> 13. Liaison. The County's primary contact for the Consultant shall be [insert name and contact information for County's primary point of contact].
 A> The primary contact at the County for the Consultant is [insert name and contact information for County's primary point of contact].


 69% 69/100 [06:46<03:03,  5.91s/it]INFO 2024-06-26 22:16:39,172 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Does the Agreement specify the termination conditions?
 I> 14. Termination. This Agreement may be terminated by either party upon thirty (30) days' written notice to the other. The County may also terminate this Agreement immediately if the Consultant, in the County's sole judgment, breaches any material term or condition of this Agreement. Upon termination, the Consultant shall be paid for all Services performed up to the effective date of termination.
 A> Yes, the Agreement specifies that either party can terminate the Agreement upon thirty (30) days' written notice or immediately if the Consultant breaches any material term or condition of the Agreement. Upon termination, the Consultant shall be paid for all Services performed up to the effective date of termination.

 Q> What is the nature of the services that the Consultant will render under the Agreement?
 I> 2. Services. The Consultant shall provide consulting services to the County related to the development of the \_\_\_\_\_. The Consultant shall provide these Services in accordance with the Work Statement and Work Schedule, which are attached hereto as Exhibit A.
 A> Under the Agreement, the Consultant will provide consulting services related to the development of the project specified in Exhibit A.


 71% 71/100 [06:57<02:46,  5.73s/it]INFO 2024-06-26 22:16:49,788 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Identify the payment structure for the services mentioned in the email agreement.
 I> 9. Payment. The County shall pay the Consultant a total fee of $150,000 for the Services under this Agreement, plus any reasonable expenses approved in advance by the County. The County shall pay the Consultant an initial payment of $50,000 upon execution of this Agreement. The Consultant shall invoice the County for the remaining $100,000 in four equal installments due at the completion of each quarter of the Services.
 A> The payment structure for the services mentioned in the email agreement is that the County shall pay the Consultant a total fee of $150,000, with an initial payment of $50,000 upon execution of the agreement. The remaining $100,000 will be paid in four equal installments due at the completion of each quarter of the Services.

 Q> What is the main subject of the email that contains the services agreement?
 I> 
 A> Based on the context, the main subject of the email that contains the services agreement is a collaboration between the County and the Consultant to perform certain Services, as outlined in the agreement.


 73% 73/100 [07:07<02:30,  5.56s/it]INFO 2024-06-26 22:17:00,104 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What are the steps to follow if there is a dispute between the parties?
 I> 15. **Dispute Resolution.** Any disputes arising out of this Agreement shall be resolved in accordance with the dispute resolution provisions of the Colorado Uniform Arbitration Act, C.R.S. § 13-22-201 et. seq. (the "Act"). In addition to the provisions of the Act, the following provisions shall apply:

 A. The arbitration shall be conducted by a single arbitrator and shall be administered by the American Arbitration Association ("AAA") in accordance with its then governing rules;

 B. The arbitrator shall have the power to award any legal or equitable remedy, including injunctive relief;

 C. Either party may apply to the district court of the County for an order to compel arbitration in accordance with the Act and the provisions of this Agreement. The decision of the court shall be final and binding;

 D. The arbitrator shall issue a written decision that sets forth the essential findings and conclusions on which the award or decision is based. The arbitrator shall have the power to rule on his or her own jurisdiction, including the existence, scope, or validity of the arbitration agreement;

 E. The arbitration award shall be final and binding upon the parties. Judgment upon the award may be entered in any court having jurisdiction thereof;

 F. The parties shall equally share the costs and fees of arbitration, including the arbitrator's fees, except as may be required by law or decided by the arbitrator; and

 G. The parties shall maintain the confidentiality of the arbitration proceedings and the award, to the extent permitted by law.
 A> Any disputes arising out of this Agreement shall be resolved in accordance with the dispute resolution provisions of the Colorado Uniform Arbitration Act, C.R.S. § 13-22-201 et. seq. The parties shall maintain the confidentiality of the arbitration proceedings and the award, to the extent permitted by law. Either party may apply to the district court of the County for an order to compel arbitration in accordance with the Act and the provisions of this Agreement. The arbitration award shall be final and binding upon the parties. The parties shall equally share the costs and fees of arbitration, including the arbitrator's fees, except as may be required by law or decided by the arbitrator.


 74% 74/100 [07:16<02:40,  6.16s/it]INFO 2024-06-26 22:17:09,074 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Describe the scope of services that the Consultant is required to provide to the County.
 I> 22. Scope of Services. Consultant agrees to provide the following services: a. Configuration and customization of the software system; b. Implementation of the software system, including data migration and integration with the County’s existing systems; c. Training and support for County staff on the use of the software system; d. Maintenance and updates to the software system for a period of thirty (30) days following the completion of implementation.
 A> The scope of services involves configuration and customization of the software system, implementation of the software system with data migration and integration with the County’s existing systems, training and support for County staff on the use of the software system, and maintenance and updates to the software system for 30 days following completion.

 Q> What are the two conditions under which the Agreement between the Consultant and the County can be terminated?
 I> 28. Termination. This Agreement may be terminated by either party upon written notice to the other party if the other party: a. Fails to perform any material obligations under this Agreement, including but not limited to the development, implementation and delivery of the software system as described in this Agreement; or b. Breaches any term or condition of this Agreement, including but not limited to the confidentiality provisions of this Agreement.
 A> The Agreement between the Consultant and the County can be terminated if the other party fails to perform any material obligations or breaches any term or condition of the Agreement, including the confidentiality provisions.


 76% 76/100 [07:27<02:23,  5.97s/it]INFO 2024-06-26 22:17:20,274 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Who is the recipient of the email and what is the subject of the email?
 I> Dear [John Doe](mailto:[email protected]),

 I am writing to follow up on our recent meeting regarding the new project. I have attached the proposal for your review.

 Best regards,
 [Jane Smith](mailto:[email protected])
 A> The recipient of the email is John Doe and the subject of the email is not explicitly stated in the provided content.

 Q> What is the first deliverable that the Consultant must deliver according to the agreement?
 I> 1. Deliverables. The Consultant shall deliver the following Deliverables: (a) A complete and detailed proposal outlining the Services to be provided, the methodology to be used, the timeline for completion, and the estimated costs. (b) All necessary permits, approvals, and authorizations required for the Services. (c) Regular progress reports detailing the status of the Services, any issues encountered, and any changes made to the original plan. (d) The final product or result of the Services, in the format and medium specified in the Agreement.
 A> The first deliverable that the Consultant must deliver according to the agreement is a complete and detailed proposal outlining the Services to be provided, the methodology to be used, the timeline for completion, and the estimated costs.


 78% 78/100 [07:38<02:07,  5.80s/it]INFO 2024-06-26 22:17:31,152 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Can you identify the task associated with the due date of October 15, 2022?
 I> Tasks and corresponding due dates:

 a. Project A: August 1, 2022

 b. Project B: October 15, 2022

 c. Project C: January 3, 2023
 A> Project B is due on October 15, 2022.

 Q> What is the payment due date if invoice is received on July 3rd, 2022?
 I> Payment terms: Payment of invoices will be due within twenty-five (25) days of the receipt thereof.
 A> The payment will be due on July 28, 2022 (25 days after July 3rd, 2022).


 80% 80/100 [07:48<01:49,  5.50s/it]INFO 2024-06-26 22:17:40,837 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Who is responsible for the payment of expenses and costs associated with the project?
 I> The County shall pay all expenses and costs associated with Consultant's work on the project, including but not limited to travel expenses, per diem, and fees for subcontractors or consultants engaged in the performance of the Contract.
 A> The County is responsible for paying all expenses and costs associated with the Consultant's work on the project, including but not limited to travel expenses, per diem, and fees for subcontractors or consultants engaged in the performance of the Contract.

 Q> What are the terms and conditions regarding the protection of confidential information?
 I> Consultant agrees to keep confidential all information disclosed to Consultant by the County, its officers, employees, or agents, whether orally, visually, or in writing that is not otherwise generally available to the public.
 A> The Consultant agrees to keep confidential all information disclosed to them by the County, its officers, employees, or agents, whether orally, visually, or in writing, that is not otherwise generally available to the public.


 82% 82/100 [07:58<01:36,  5.35s/it]INFO 2024-06-26 22:17:50,909 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What type of information is required in the Monthly Status Reports?
 I> 1. Reports. The Consultant shall submit a monthly status report ("Monthly Status Report") to the Project Manager. The Monthly Status Report shall include: (a) the status of allTasks and Deliverables assigned to the Consultant during the preceding month, including any changes in schedules and budgets; and (b) any issues, challenges, or additional resources requested by the Consultant in performing the Services.
 A> The Monthly Status Reports should include the status of all tasks and deliverables assigned to the Consultant during the preceding month, changes in schedules and budgets, and any issues, challenges, or additional resources requested by the Consultant in performing the Services.

 Q> Who are the parties responsible for the maintenance of the system?
 I> 2. Responsibilities. The Consultant shall be responsible for the following services during the Term: (a) installing and configuring the software system; (b) providing training and documentation to the County’s personnel; (c) performing any necessary maintenance and troubleshooting of the software system during normal business hours.
 A> The Consultant is responsible for installing and configuring the software system, providing training and documentation to the County’s personnel, and performing any necessary maintenance and troubleshooting of the software system during normal business hours.


 84% 84/100 [08:09<01:25,  5.33s/it]INFO 2024-06-26 22:18:01,455 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What are the specific services that the Consultant is expected to deliver in this project?
 I> 1. Objectives

 A. To provide expertise in the area of ___.
 B. To assist County staff with the development of ___.
 C. To provide in-depth analysis and recommendations concerning ___.

 2. Specific Services

 A. Conduct a thorough review and inventory of ___.
 B. Prepare and submit a written report and presentation regarding ___.
 C. Participate in ___.
 D. Schedule and facilitate ___.
 E. Provide technical assistance and support to ___.
 F. Attend all required County staff meetings related to ___.
 A> The Consultant is expected to provide expertise in the area of the project, assist County staff with the development of necessary documents, provide in-depth analysis and recommendations, conduct a thorough review and inventory of relevant materials, prepare and submit a written report and presentation, participate in relevant meetings, schedule and facilitate necessary meetings, provide technical assistance and support, and attend all required County staff meetings related to the project.


 85% 85/100 [08:15<01:21,  5.46s/it]INFO 2024-06-26 22:18:07,524 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Which specific issues did the Consultant encounter during the Services, as mentioned in the progress reports?
 I> 3. Progress Reports. The Consultant shall provide Regular Progress Reports detailing the status of the Services, any issues encountered, and any changes made to the original plan. During the Services, the Consultant encountered issues with obtaining the necessary permits, delays in receiving the required data from the Client, and changes in the Client's requirements.
 A> During the Services, the Consultant encountered issues with obtaining the necessary permits, delays in receiving the required data from the Client, and changes in the Client's requirements.

 Q> Which is the format and medium specified in the Agreement for delivering the final product?
 I> 4. Final Product. The Consultant shall deliver the final product or result of the Services, in the format and medium specified in the Agreement. The format specified in the Agreement is a digital file and the medium specified is email.
 A> The format specified in the Agreement for delivering the final product is a digital file and the medium specified is email.


 87% 87/100 [08:25<01:08,  5.31s/it]INFO 2024-06-26 22:18:17,534 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What are the Client's instructions for the Consultant regarding the data analysis?
 I> 2. Scope of Work. The Consultant shall provide consulting services for the Data Analysis Project ("Project") and shall conduct a thorough analysis of the data provided by the Client. The Client instructs the Consultant to pay special attention to identifying patterns, anomalies, and trends in the data, and to provide insights and recommendations based on the results of the analysis.
 A> The Client has instructed the Consultant to conduct a thorough analysis of the data provided, paying special attention to identifying patterns, anomalies, and trends, and to provide insights and recommendations based on the results of the analysis.

 Q> Can the Consultant invoice the Client for services provided on a monthly basis, as outlined in the agreement?
 I> 4. Invoices. The Consultant shall invoice the Client for the Services provided on a monthly basis, and all invoices shall be due and payable within thirty (30) days of receipt.
 A> Yes, as outlined in the agreement, the Consultant can invoice the Client for services provided on a monthly basis, and all invoices shall be due and payable within thirty (30) days of receipt.


 89% 89/100 [08:35<00:58,  5.30s/it]INFO 2024-06-26 22:18:28,081 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> Explain the procedure for requesting a change order in the agreement.
 I> 2. CHANGES TO AGREEMENT. Consultant may request a change order by providing the County with a written request that includes a detailed description of the requested change, the reason for the change, and any additional costs or fees resulting from the change. The County will review the request and will provide Consultant with a written response within seven (7) business days. The written response will either approve or deny the change order request.
 A> To request a change order, Consultant should provide the County with a written request including the requested change's description, reason, and additional costs. The County will review and respond within seven (7) business days, either approving or denying the request.

 Q> Which party is responsible for conflicts arising during the performance of this Agreement?
 I> 4. TERMINATION. Consultant may terminate this Agreement at any time by giving the County written notice of not less than sixty (60) days. County may terminate this Agreement at any time in the event that Consultant violates the terms of this Agreement or fails to produce a result that meets the specifications of this Agreement. In the event of termination, payments will be made to Consultant for all work performed up to the date of termination.
 A> The parties themselves are responsible for resolving conflicts arising during the performance of this Agreement. However, the County may terminate the Agreement if Consultant violates the terms or fails to meet the specified results.


 91% 91/100 [08:46<00:48,  5.34s/it]INFO 2024-06-26 22:18:38,970 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 INFO 2024-06-26 22:18:42,820 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What methods does the Consultant propose to use for the Services?
 I> 1. Deliverables. The Consultant shall deliver the following Deliverables: (a) A complete and detailed proposal outlining the Services to be provided, the methodology to be used, the timeline for completion, and the estimated costs. (b) All necessary permits, approvals, and authorizations required for the Services. (c) Regular progress reports detailing the status of the Services, any issues encountered, and any changes made to the original plan. (d) The final product or result of the Services, in the format and medium specified in the Agreement.
 A> According to the agreement, the Consultant proposes to use the methodology outlined in the complete and detailed proposal, which encompasses the Services to be provided, the timeline for completion, and the estimated costs.

 Q> What is the specified format for the final product of the Services?
 I> 1. Deliverables. The Consultant shall deliver the following Deliverables: (a) A complete and detailed proposal outlining the Services to be provided, the methodology to be used, the timeline for completion, and the estimated costs. (b) All necessary permits, approvals, and authorizations required for the Services. (c) Regular progress reports detailing the status of the Services, any issues encountered, and any changes made to the original plan. (d) The final product or result of the Services, in the format and medium specified in the Agreement.
 A> The format for the final product or result of the Services is specified in the Agreement, as indicated in Deliverable (d).


 93% 93/100 [09:01<00:42,  6.02s/it]INFO 2024-06-26 22:18:54,019 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What are the deadlines for completing the project?
 I> 1. **Project Schedule.** The Consultant shall complete the work within 120 days of the Effective Date of this Agreement. The Consultant shall deliver the final product by 5:00 p.m. on the 120th day, unless otherwise agreed to in writing by the County.
 A> The Consultant shall complete the work and deliver the final product by 5:00 p.m. on the 120th day, unless otherwise agreed in writing.

 Q> Who will be responsible for training County staff on the use of the software?
 I> 1. **Training.** The Consultant shall provide training to County staff on the use of the software. The training shall be conducted by a qualified trainer, who shall be designated by the Consultant.
 A> The Consultant shall provide training to County staff on the use of the software, conducted by a qualified trainer designated by the Consultant.


 95% 95/100 [09:11<00:28,  5.69s/it]INFO 2024-06-26 22:19:03,899 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What is the deadline for the Consultant to submit the reports and presentations?
 I> 5. Deliverables. Consultant shall provide the following deliverables: (i) a written report ("Report") that summarizes the results of the Research and provides a list of recommended actions for the County to take to address the identified issues, (ii) a presentation ("Presentation") that provides an overview of the Report and the recommended actions, and (iii) any other materials specified in the Scope of Work section of this Agreement. 6. Timeline. Consultant shall deliver the Deliverables to the County no later than 45 days after the Effective Date.
 A> According to the email agreement, the Consultant is required to submit the reports and presentations to the County no later than 45 days after the Effective Date.

 Q> What happens if the Consultant fails to meet the deadline for report submission?
 I> 6. Timeline. Consultant shall deliver the Deliverables to the County no later than 45 days after the Effective Date. 7. Delay. In the event of any delay in Consultant's delivery of the Deliverables beyond the timeline set forth in this Agreement, County shall be entitled to recover from Consultant its actual damages resulting from such delay, and Consultant shall not be entitled to receive any payment under this Agreement until the Deliverables are delivered to the County.
 A> If the Consultant fails to meet the deadline for report submission, the County is entitled to recover actual damages resulting from the delay. The Consultant will not be entitled to receive any payment under the agreement until the Deliverables are delivered to the County.


 97% 97/100 [09:22<00:17,  5.71s/it]INFO 2024-06-26 22:19:15,389 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What is the service fee for Additional Services requested by the County?
 I> 6. Payment. The County shall pay Consultant for the Services specified as follows:

 A. Regular Services. Regular Services shall be compensated at the rate of $70.00 per hour.

 B. Additional Services. The County may request additional services from Consultant, which shall be compensated at the rate of $90.00 per hour.

 C. Expenses. Consultant may be reimbursed for the reasonable expenses incurred by Consultant in performing the services upon presentation of valid receipts for such expenditures.

 D. Mileage. Consultant shall be reimbursed for all travel at the current rate as established by law.

 E. Payment. Payment for all amounts due under this Section shall be due to Consultant within thirty (30) days of receipt of each invoice submitted by Consultant.
 A> The service fee for Additional Services requested by the County is $90.00 per hour.

 Q> What are the consequences for failure to comply with the reimbursement procedures?
 I> 10. Reimbursement. Consultant shall submit to the County, on a monthly basis, a request for reimbursement for all reasonable expenses incurred in performing the Services.

 A. Valid Receipts. A detailed, itemized receipt for each expense must accompany all requests for reimbursement.

 B. Timing. Reimbursement requests must be submitted no later than thirty (30) days following the date the expense was incurred.

 C. Approval. All reimbursement requests shall be subject to approval by the County's Director of Finance or designee.

 D. Consequences. Failure to comply with the reimbursement procedures may result in the County's refusal to reimburse Consultant for any such expenses.
 A> The consequences for failure to comply with the reimbursement procedures include the County's refusal to reimburse Consultant for any such expenses.


 99% 99/100 [09:35<00:05,  5.84s/it]INFO 2024-06-26 22:19:27,709 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 INFO 2024-06-26 22:19:29,998 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->services_agreement->plain_text
 Q> What are the deliverables required by the Consultant in this agreement?
 I> 5. Deliverables. Consultant shall provide the following deliverables: (i) a written report ("Report") that summarizes the results of the Research and provides a list of recommended actions for the County to take to address the identified issues, (ii) a presentation ("Presentation") that provides an overview of the Report and the recommended actions, and (iii) any other materials specified in the Scope of Work section of this Agreement.
 A> The deliverables required from the Consultant in this agreement are a written report that summarizes the results of the Research and provides a list of recommended actions, a presentation that provides an overview of the Report and the recommended actions, and any other materials specified in the Scope of Work section.

 Q> How long does the Consultant have to submit the deliverables to the County?
 I> 6. Timeline. Consultant shall deliver the Deliverables to the County no later than 45 days after the Effective Date.
 A> The Consultant has 45 days after the Effective Date to submit the deliverables to the County.


 101it [09:47,  5.97s/it]            
 101it [09:47,  5.82s/it]
 INFO 2024-06-26 22:19:40,211 generate_data.py:609: generate_data 101 instructions generated, 30 discarded due to format (see /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/services_agreement/plain_text/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T22_09_52.log), 0 discarded due to rouge score
 INFO 2024-06-26 22:19:40,211 generate_data.py:613: generate_data Generation took 587.89s
 Completed 88.9 KiB/222.2 KiB (732.8 KiB/s) with 4 file(s) remaining
 upload: ../outputtopush/train_Mixtral-8x7B-Instruct-v0_2024-06-26T22_09_52.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/services_agreement/plain_text/train_Mixtral-8x7B-Instruct-v0_2024-06-26T22_09_52.jsonl
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 Completed 113.8 KiB/222.2 KiB (846.5 KiB/s) with 3 file(s) remaining
 upload: ../outputtopush/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T22_09_52.log to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/services_agreement/plain_text/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T22_09_52.log
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 Completed 132.6 KiB/222.2 KiB (855.7 KiB/s) with 2 file(s) remaining
 upload: ../outputtopush/test_Mixtral-8x7B-Instruct-v0_2024-06-26T22_09_52.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/services_agreement/plain_text/test_Mixtral-8x7B-Instruct-v0_2024-06-26T22_09_52.jsonl
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 Completed 222.2 KiB/222.2 KiB (824.1 KiB/s) with 1 file(s) remaining
 upload: ../outputtopush/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T22_09_52.json to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/services_agreement/plain_text/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T22_09_52.json
 compositional_skills/extraction/receipt/reasoning/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/extraction/receipt/reasoning/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/receipt/reasoning --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T22:19:42Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/extraction/receipt/reasoning/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 22:19:50,875 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What is the individual food expense for each person at bartaco?
 I> 
 A> Luke (You) spent $262.65 on food, David spent $17.52, Abhishek spent $11.91, Kate spent $17.52, Nathan spent $18.48, Kai spent $0.00, Aldo spent $7.99, Shiv spent $0.00, Rameswar spent $4.00, and Ruchir spent $3.11.

 Q> Was there any discount offered on the receipt, and if so, what was it?
 I> ## Thanks for tipping, Luke

 Here's your updated receipt for bartaco (Seaport).

 ## Total

 ## $289.71

 | Subtotal   | $239.99  |
 |---------------|-----------|
 | Service Fee  | $14.12  |
 | Tax      | $16.05  |
 | Delivery Fee | $0.49   |
 | Tip      | $27.06  |
 | Special Offer | -$8.00  |

 ## Payments

 | Visa ····6451  | $262.65  |
 |-----------------|-----------|
 | 2/23/24 2:06 PM |      |
 | Visa ····6451  | $27.06  |
 | 2/23/24 3:06 PM |      |
 A> Yes, there was an $8.00 discount applied.


  2% 2/100 [00:11<09:39,  5.92s/it]INFO 2024-06-26 22:20:02,708 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Who paid for what at the bartaco outing?
 I> ## Here's your updated receipt for bartaco (Seaport)

 | Subtotal   | $239.99  |
 |---------------|-----------|
 | Service Fee  | $14.12  |
 | Tax      | $16.05  |
 | Delivery Fee | $0.49   |
 | Tip      | $27.06  |
 | Special Offer | -$8.00  |

 ## Items

 | Item   | Unit Cost   | Qty    | Subtotal    | Payer         |
 |---------------|---------------|-----------|-----------|---------------|
 | Chips: Guac   | $12.66     | 1         | $12.66     | **Luke**      |
 | Margs     | $14.99     | 2         | $29.98     | **David**    |
 | Shrimp Tacos | $11.99     | 2         | $23.98     | **Abhishek** |
 | Chicken Tacos | $8.99     | 2         | $17.98     | **Kate**     |
 | Pork Tacos  | $9.99     | 1         | $9.99      | **Nathan**   |
 | Soft Drinks  | $1.99     | 1         | $1.99      | **Kai**      |
 | Sangria     | $11.99     | 1         | $11.99     | **Aldo**     |
 | Dips Combo   | $7.65     | 1         | $7.65      | **Shiv**      |
 | Rice & Beans  | $3.99     | 1         | $3.99      | **Rameswar** |
 | Kale Salad   | $3.99     | 1         | $3.99      | **Ruchir**   |

 ## Payments

 | Visa ····6451  | $262.65  |
 |-----------------|-----------|
 | 2/23/24 2:06 PM |      |
 | Visa ····6451  | $27.06  |
 | 2/23/24 3:06 PM |      |
 A> * Luke covered the chips and guacamole.
 * David paid for 2 orders of margs.
 * Abhishek paid for 2 orders of Shrimp Tacos.
 * Kate paid for 2 orders of Chicken Tacos.
 * Nathan paid for 1 order of Pork Tacos.
 * Kai paid for 1 order of a Soft Drink.
 * Aldo paid for 1 order of Sangria.
 * Shiv didn't pay for anything.
 * Rameswar paid for 1 order of Rice & Beans.
 * Ruchir paid for 1 order of Kale Salad.
 * Luke paid for the Service Fee, Tax, Delivery Fee, and $1.66 of Tip.
 * David paid for the remaining $25.40 of Tip.

 Q> What was the largest expense for each person, not including tips, at the bartaco outing?
 I> 
 A> * Luke (You) had the largest spend on food/drinks with $12.66 and the service fee at $14.12.
 * David spent $29.98 on margs.
 * Abhishek spent $23.98 on Shrimp Tacos.
 * Kate spent $17.98 on Chicken Tacos.
 * Nathan spent $9.99 on Pork Tacos.
 * Kai spent $1.99 on a Soft Drink.
 * Aldo spent $11.99 on Sangria.
 * Shiv didn't have any expenses.
 * Rameswar spent $3.99 on Rice & Beans.
 * Ruchir spent $3.99 on Kale Salad.


  4% 4/100 [00:31<13:09,  8.22s/it]INFO 2024-06-26 22:20:22,379 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What was the total cost for each customer, and who paid tip?
 I> ## Here's your updated receipt for bartaco (Seaport)

 | Subtotal   | $239.99  |
 |---------------|-----------|
 | Service Fee  | $14.12  |
 | Tax      | $16.05  |
 | Delivery Fee | $0.49   |

 ## Payments

 | Visa ····6451  | $241.06  |
 |-----------------|-----------|
 | Visa ····5439  | $57.74  |
 | Visa ····8923  | $148.69  |
 A> * Luke paid a total of $140.18 ($126.66 for items, $10.18 for tip, $1.49 for tax, $0.49 for delivery fee and $1.46 for service fee).
 * David paid a total of $62.11 ( $29.98 for items, $31.13 for tip, $1.49 for tax, and $0.49 for service fee).
 * Rameswar paid a total of $174.50 ( $3.99 for item, $170.43 for tip, $1.49 for tax, and $0.49 for delivery fee and $0.10 for service fee).

 Q> What was each customer's contribution to the subtotal?
 I> ## Here's your updated receipt for bartaco (Seaport)

 | Subtotal   | $239.99  |
 |---------------|-----------|
 | Service Fee  | $14.12  |
 | Tax      | $16.05  |
 | Delivery Fee | $0.49   |

 ## Details

 | Customer    | Item         | Subtotal    |
 |---------------|---------------|---------------|
 | Luke         | Chips: Guac  | $12.66        |
 | Luke         | Margaritas   | $14.99        |
 | Abhishek     | Chips: Salsa  | $5.30        |
 | David        | Margaritas   | $14.99        |
 | David        | Tacos        | $11.79        |
 | Rameswar     | White Rice   | $3.99        |
 | Luke         | 7 Layer Dip  | $7.65        |
 | Rameswar     | Beans       | $3.99        |
 A> * Luke contributed $35.60 to the subtotal, Abhishek contributed $5.30, David contributed $26.78, and Rameswar contributed $7.98.


  6% 6/100 [00:47<12:44,  8.13s/it]INFO 2024-06-26 22:20:38,436 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Which items did Luke order from bartaco and how much did he pay for them?
 I> 
 A> Luke ordered tuna tartare, baja fish tacos, chicken burrito, and a watermelon margarita from bartaco. The total cost for these items was $126.66.

 Q> Explain how the amount of $14.12 was calculated for service fees at bartaco.
 I> ## Thanks for tipping, Luke

 Here's your updated receipt for bartaco (Seaport).

 ## Total

 ## $289.71

 ...

 ## Payments

 | Visa ····6451  | $262.65  |
 |-----------------|-----------|
 | 2/23/24 2:06 PM |      |
 | Visa ····6451  | $27.06  |
 | 2/23/24 3:06 PM |      |
 A> The service fee of $14.12 is a 10% charge on the total food and drink cost ($239.99) before tax and any discounts or additional charges.


  8% 8/100 [00:58<10:46,  7.03s/it]INFO 2024-06-26 22:20:49,111 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Calculate the individual cost of each item purchased.
 I> ## Here's your updated receipt for bartaco (Seaport)

 | Items | Cost     |
 |---------------|-----------|
 | Chips: Guac   | $12.66     |
 | Margs     | $14.99     |
 | Shrimp Tacos | $11.99     |
 | Chicken Tacos | $8.99     |
 | Pork Tacos  | $9.99     |
 | Soft Drinks  | $1.99     |
 | Sangria     | $11.99     |
 | Dips Combo   | $7.65      |
 | Rice & Beans  | $3.99     |
 | Kale Salad   | $3.99     |
 A> * The cost of Chips: Guac is $12.66, Margs is $14.99, Shrimp Tacos is $11.99, Chicken Tacos is $8.99, Pork Tacos is $9.99, Soft Drinks is $1.99, Sangria is $11.99, Dips Combo is $7.65, Rice & Beans is $3.99, and Kale Salad is $3.99.

 Q> Determine the amount paid for taxes, delivery fee and service fee.
 I> 
 A> * The delivery fee is $0.49, the service fee is $14.12, and the tax is $16.05.


 10% 10/100 [01:10<10:00,  6.67s/it]INFO 2024-06-26 22:21:01,161 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> For the kale salad, can you provide details on how it was prepared?
 I> 
 A> - Kale Salad was prepared with kale, lemon juice, olive oil, salt, and pepper.

 Q> If anyone didn't buy any food item and only purchased beverages, whose name would that be?
 I> 
 A> - Kai bought a soft drink but no food items.


 12% 12/100 [01:19<08:38,  5.89s/it]INFO 2024-06-26 22:21:09,933 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What is the hub address on the AmazonSmile receipt?
 I> ## Here's your AmazonSmile receipt for Prime Wardrobe

 **AmazonSmile**

 Thank you for shopping!

 **Order Details**
 Order ID: 352-1134010-6771022
 Order Date: Feb 22, 2022

 **Delivery Address**
 [John Doe](mailto:[email protected])
 711 W 5th St, Apt 34B
 Los Angeles, CA 90014
 310-555-XXXX

 **Shipping Option**
 Free Two-Day Shipping

 **Billing Address**
 [John Doe](mailto:[email protected])
 711 W 5th St, Apt 34B
 Los Angeles, CA 90014
 310-555-XXXX

 **Items in Your Order**

 | Item | Quantity | Customer Reviews |
 | --- | --- | --- |
 | NIKE Men's One React 2 Running Shoe | 1 | 4.5 &#9733;&#9733;&#9733;&#9733;&#9734; |
 | The North Face Men's Venture 2 Half-Zip Fleece Jacket | 1 | 4.4 &#9733;&#9733;&#9733;&#9733;&#9734; |

 **Prime Wardrobe Summary**
 - Return item(s) to receive full refund
 - Keep item(s) to pay the price indicated

 **Charges**
 - Subtotal: $176.56
 - Shipping: Free
 - Tax: $0.00
 - **hub_address:** Amazon Hub Locker, 801 S Hill St, Los Angeles, CA 90015
 A> * The hub address on the AmazonSmile receipt is Amazon Hub Locker, 801 S Hill St, Los Angeles, CA 90015.

 Q> Calculate the subtotal, tax, and shipping for this purchase.
 I> ## DICK'S Sporting Goods Receipt

 **DICK'S Sporting Goods**

 Brought to you by Sports

 1002 Galleria Blvd, Houma, LA 70360, USA
 (985) 879-2246

 **Transaction Summary**

 | Date&Time | Item Description | Amount |
 | --- | --- | --- |
 | 2/22/2022 6:23:27 PM | ASICS Men's GEL-Venture 6 Running Shoe-Peat/Black/Bahia Blue | $60.00 |
 | 2/22/2022 6:23:27 PM | CRAFT All-Year-Round Crew Socks, 6Pair   | $60.00 |
 | 2/22/2022 6:23:27 PM | Wilson NCAA® Solution Game Basketball | $39.99 |
 |   |  |  |
 | **Subtotal:** |  | $159.99** |
 | **Tax:** | **State: 4.5%** | **$7.13** |
 |  | **LA County: 2.0%** |  |
 |  | **City: 1.5%** |  |
 |  | **Special Tax:** |  |
 | **Total:** |  | **$167.12** |
 | **Cash Tendered:** |  | **$168.00** |
 | **Change: $0.88** |  |  |
 | **VISA ****XXXX-XXXX-XXXX-1234** | **Autho #: 6A4MD9** | **Amount Approved: $168.00** |
 A> * The subtotal for this purchase is $159.99, the tax is $7.13, and the shipping is $0.00.


 14% 14/100 [01:36<09:48,  6.84s/it]INFO 2024-06-26 22:21:27,526 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What is the subtotal for the purchase on the receipt from Target?
 I> ## Receipt

 ---

 | **Target Receipt** |
 | --- |
 | March 3, 2022 |
 | Receipt #: 31693265 |
 | Cashier: Rebecca G. |
 | --- |
 | **Item** | **Price (per unit)** | **Quantity** | **Subtotal** |
 | --- | --- | --- | --- |
 | Apple iPhone 11 Pro Max | $1,099.99 | 1 | $1,099.99 |
 | Bose SoundLink Color Bluetooth Speaker II | $139.00 | 1 | $139.00 |
 | Apple AirPods Pro (2nd generation) | $249.00 | 1 | $249.00 |
 | Apple Care+ for iPhone 11 Pro Max | $199.00 | 1 | $199.00 |
 | --- | --- | --- | --- |
 | **Subtotal:** | **$1,726.99** | | |
 | **Tax (8.25%):** | **$140.08** | | |
 | **Total:** | **$1,867.07** | | |
 ---
 A> * The subtotal for the purchase on the receipt from Target is $1,726.99.

 Q> How many items were purchased from the receipt of Ulta Beauty?
 I> ## Receipt

 ---

 **Ulta Beauty Receipt**
 -------------------

 **Transaction Details** | **Value**
 ---------------------------|---------
 Transaction ID | 1028467192
 Date | Jan 14, 2022
 Time | 3:45 PM
 ---------------------------|---------
 **Item Details** | **Quantity** | **Price per Unit** | **Discount** | **Total**
 ----------------------------------------------------------------------
 Fenty Beauty by Rihanna Pro Filt'r Foundation | 1 | $34.00 | $0.00 | $34.00
 NARS Velvet Matte Lipstick Pencil - Dolce Vita | 1 | $28.00 | $0.00 | $28.00
 Charlotte Tilbury Eyes to Mesmerise Cream Eyeshadow | 2 | $32.00 | $0.00 | $64.00
 Anastasia Beverly Hills Dipbrow Pomade | 1 | $18.00 | $0.00 | $18.00
 Living Proof Restore Instant Protection Spray | 1 | $28.00 | $7.00 | $21.00
 ----------------------------------------------------------------------
 A> * A total of 6 items were purchased from the Ulta Beauty receipt.


 16% 16/100 [01:51<09:45,  6.97s/it]INFO 2024-06-26 22:21:42,009 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Identify which item(s) were delivered and the cost for each.
 I> ## Receipt for Big Burger Wagon

 | Item                    | Quantity | Cost Each | Cost     |
 |--------------------------|----------|------------|-----------|
 | Bacon Cheeseburger      | 1       | $4.99     | $4.99    |
 | Chips                   | 1       | $1.50     | $1.50    |
 | Soft Drink               | 1       | $1.75     | $1.75    |
 | Veggie Burger           | 2       | $5.50     | $11.00  |
 | Large Fries             | 1       | $2.00     | $2.00    |
 | Free sample of chili     | 1       | $0.00     | $0.00    |
 A> The Bacon Cheeseburger, Chips, and Soft Drink were delivered, with the following cost breakdown:

 * Bacon Cheeseburger: $4.99
 * Chips: $1.50
 * Soft Drink: $1.75

 The Veggie Burger and Large Fries were ordered, but not delivered.

 Q> What was the discount or special offer applied on the provided receipt?
 I> 
 A> The provided receipt contains an $8.00 discount or special offer applied, as indicated on the 'Special Offer' line. The specific description may vary depending on the promotion.


 18% 18/100 [02:03<09:17,  6.80s/it]INFO 2024-06-26 22:21:54,839 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Did Luke get a discount for his bartaco order? If yes, what's the value and type of the discount?
 I> ## Thanks for tipping, Luke

 Here's your updated receipt for bartaco (Seaport).
 ## Total

 ## $289.71

 | Subtotal   | $239.99  |
 |---------------|-----------|
 | Service Fee  | $14.12  |
 | Tax      | $16.05  |
 | Delivery Fee | $0.49   |
 | **Discount** | **-$8.00**|
 | Tip      | $27.06  |
 | Special Offer | -$8.00  |

 ## Payments

 | Visa ····6451  | $262.65  |
 |-----------------|-----------|
 | 2/23/24 2:06 PM |      |
 | Visa ····6451  | $27.06  |
 | 2/23/24 3:06 PM |      |
 A> Yes, Luke received an $8 discount on his bartaco order. It is under the "Special Offer" category, which could be a promotional code, a referral discount, or other types of discounts that have a special designation on the receipt.

 Q> What did bartaco charge for delivery and how many meals was this order for?
 I> ## Thanks for tipping, Luke

 Here's your updated receipt for bartaco (Seaport).

 ## Total

 ## $289.71

 | Subtotal   | $239.99  |
 |---------------|-----------|
 | Service Fee  | $14.12  |
 | **Tax      **| $16.05  |
 | **Delivery Fee** | **$0.49** |
 | Tip      | $27.06  |
 | Special Offer | -$8.00  |

 ## Items

 | Name        | Qty | Price | 
 |---------------|-----|-------|
 | Tuna Tartare | 1  | $14.99|
 | Baja Fish Tacos | 2 | $9.98 |
 | Chicken Burrito | 1  | $11.99|
 | Watermelon Marg | 1  | $11.00|
 | Guacamole   | 1  | $5.00 |
 | Chips       | 1  | $5.00 |

 ## Payments

 | Visa ····6451  | $262.65  |
 |-----------------|-----------|
 | 2/23/24 2:06 PM |      |
 | Visa ····6451  | $27.06  |
 | 2/23/24 3:06 PM |      |
 A> Bartaco charged $0.49 for the delivery of this order, which consists of 6 meals based on the items section: tuna tartare, baja fish tacos (2 pieces), chicken burrito, watermelon margarita, guacamole, and chips.


 20% 20/100 [02:20<09:36,  7.20s/it]INFO 2024-06-26 22:22:11,061 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What is the charge for Shiv's order?
 I> 
 A> * The charge for Shiv's order is $7.65 for the Dips Combo.


 21% 21/100 [02:25<09:02,  6.87s/it]INFO 2024-06-26 22:22:16,406 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Identify the tax amount added to Luke's bill at bartaco and the corresponding tax rate.
 I> ## Thanks for tipping, Luke

 Here's your updated receipt for bartaco (Seaport).

 ## Total

 ## $289.71

 ...

 ## Tax

 ## $6.98

 ...
 A> The tax amount added to Luke's bill at bartaco is $6.98, which corresponds to a tax rate of approximately 2.40%.

 Q> How many items did Luke order in total, and what is the total cost of these items?
 I> 
 A> Luke ordered a total of 4 items from bartaco, which include tuna tartare, baja fish tacos, chicken burrito, and watermelon margarita. The total cost of these items is $126.66.


 23% 23/100 [02:35<07:56,  6.19s/it]INFO 2024-06-26 22:22:26,181 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Derive the amount owed for the restaurant visit by Luke.
 I> 
 A> Luke owed $140.18 for his restaurant visit to bartaco (Seaport). This cost consists of $126.66 for items, $10.18 for tip, $1.49 for tax, $0.49 for delivery fee, and $1.46 for service fee.

 Q> Identify which payment method was used to cover the delivery fee.
 I> ## Here's your updated receipt for bartaco (Seaport)

 ...

 ## Payments

 | Visa ····6451  | $262.65  |
 |-----------------|-----------|
 | Visa ····6451  | $27.06  |
 A> The delivery fee of $0.49 was paid by the Visa card ending in 6451, as there's more than one payment with the same card.


 25% 25/100 [02:45<07:17,  5.84s/it]INFO 2024-06-26 22:22:36,412 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Retrieve the amount spent on a given food type, for example, "vegetarian."
 I> ## Receipt for Green Garden Cafe

 | Item                    | Quantity | Cost Each | Cost     |
 |--------------------------|----------|------------|-----------|
 | Vegan Curry             | 1       | $12.95     | $12.95    |
 | Vegan Tofu Stir Fry      | 1       | $13.95     | $13.95    |
 | Veggie Sushi Rolls       | 2       | $6.50     | $13.00   |
 | Beef Teriyaki           | 1       | $15.95     | $15.95    |
 | Large Side Salad         | 1       | $4.50     | $4.50    |
 A> $30.45 was spent on vegetarian options.

 Q> Which particular item did the requestor get the most of, and at what cost?
 I> ## Receipt for Salty Sailor Fish Restaurant

 | Item                    | Quantity | Cost Each | Cost     |
 |--------------------------|----------|------------|-----------|
 | Shrimp Tempura           | 3       | $5.95     | $17.85   |
 | Grilled Salmon           | 1       | $12.50    | $12.50   |
 | Crab Cake                | 1       | $9.95     | $9.95    |
 | Clam Chowder            | 2       | $7.95     | $15.90   |
 | Ceviche Tasting         | 1       | $12.50    | $12.50   |
 A> John had the most Shrimp Tempura, with a total cost of $17.85.


 27% 27/100 [03:00<07:41,  6.32s/it]INFO 2024-06-26 22:22:51,097 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Look at the receipt and disclose the time the first payment was made.
 I> ## Thanks for tipping, Ana

 Here's your updated receipt for the delicious meal you had at Cafe Europa!

 ## Total

 ## $121.58

 | Subtotal   | $99.95  |
 |---------------|-----------|
 | Service Fee  | $0.00  |
 | Tax      | $13.94  |
 | Tip      | $17.73  |

 ## Payments

 | Visa ····0389  | $103.82  |
 |-----------------|-----------|
 | 2/21/24 6:30 PM |      |
 | Visa ····0389  | $17.73  |
 | 2/21/24 6:31 PM |      |
 A> The first payment on the receipt was made at 6:30 PM.

 Q> On the given receipt, what is the total service fee without considering tax or any other additional cost?
 I> 
 A> The total service fee without tax or any other additional costs is $0.00, as shown on the 'Service Fee' line.


 29% 29/100 [03:11<07:10,  6.07s/it]INFO 2024-06-26 22:23:02,137 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> How many separate payments were made for this receipt and what were the amounts and payment types?
 I> ## Thanks for tipping, Luke

 Here's your updated receipt for bartaco (Seaport).

 ## Total

 ## $289.71

 | Subtotal   | $239.99  |
 |---------------|-----------|
 | Service Fee  | $14.12  |
 | Tax      | $16.05  |
 | Delivery Fee | $0.49   |
 | Tip      | $27.06  |
 | Special Offer | -$8.00  |

 ## Payments

 | Visa ····6451  | $262.65  |
 |-----------------|-----------|
 | 2/23/24 2:06 PM |      |
 | Visa ····6451  | $27.06  |
 | 2/23/24 3:06 PM |      |
 A> Two separate payments were made. The first payment was $262.65 using Visa ····6451 at 2:06 PM on 2/23/24, and the second payment was $27.06 using Visa ····6451 at 3:06 PM on 2/23/24.

 Q> What taxes were applied to this receipt, and what were their respective amounts?
 I> 
 A> The taxes applied to this receipt are:
 * Sales Tax: $16.05
 * Service Tax: $14.12


 31% 31/100 [03:23<06:58,  6.07s/it]INFO 2024-06-26 22:23:14,258 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What type of meat did Luke order in his Chicken Burrito from bartaco?
 I> ## Receipt for bartaco

 | Item                    | Quantity | Cost Each | Cost     |
 |--------------------------|----------|------------|-----------|
 | Tuna Tartare            | 1       | $14.00    | $14.00   |
 | Baja Fish Tacos          | 2       | $4.50     | $9.00    |
 | Chicken Burrito          | 1       | $9.25     | $9.25    |
 | Watermelon Margarita     | 1       | $10.50    | $10.50   |
 A> In his Chicken Burrito from bartaco, Luke ordered chicken.

 Q> Why was the order from Foodie Palace not delivered?
 I> ## Receipt for Foodie Palace

 | Item                    | Quantity | Cost Each | Cost     |
 |--------------------------|----------|------------|-----------|
 | Egg Fried Rice           | 1       | $7.25     | $7.25    |
 | Kung Pao Chicken        | 1       | $12.50    | $12.50   |
 | Soup Dumplings (10 pcs)| 2       | $6.50     | $13.00   |
 A> It is not explicitly mentioned in the receipt why the order from Foodie Palace was not delivered. Possible reasons might include the restaurant being out of stock, a request for pick-up, or a technical error in the delivery process.


 33% 33/100 [03:36<06:57,  6.24s/it]INFO 2024-06-26 22:23:27,512 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 INFO 2024-06-26 22:23:32,644 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What is the total price of items Luke ordered at bartaco, before tax and fees?
 I> ## Thanks for the update, Luke

 Here's your final receipt for bartaco (Seaport):
 ...

 ## Items

 * 2 x Caesar Salad, $12.75 each
 * Grilled & Chili Lime Avocado, $5.00
 * Total **Cost** | **$33.25** |
 A> The total price of items Luke ordered at bartaco, before tax and fees, is $30.75 ($33.25 with Chili Lime Avocado order).


 34% 34/100 [03:48<07:55,  7.21s/it]INFO 2024-06-26 22:23:39,164 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What services or items were offered for free or at a discount during the transaction with bartaco?
 I> ## Thanks for tipping, Luke

 Here's your updated receipt for bartaco (Seaport).

 ## Total

 ## $289.71

 | Subtotal   | $239.99  |
 |---------------|-----------|
 | Service Fee  | $14.12  |
 | Tax      | $16.05  |
 | Delivery Fee | $0.49   |
 | Tip      | $27.06  |
 | Special Offer | -$8.00  |

 ## Payments

 | Visa ····6451  | $262.65  |
 |-----------------|-----------|
 | 2/23/24 2:06 PM |      |
 | Visa ····6451  | $27.06  |
 | 2/23/24 3:06 PM |      |
 A> An $8.00 discount was applied during the transaction with bartaco.

 Q> What was the original cost of the items ordered from bartaco before any discounts were applied?
 I> ## Thanks for tipping, Luke

 Here's your updated receipt for bartaco (Seaport).

 ## Total

 ## $289.71

 | Subtotal   | $239.99  |
 |---------------|-----------|
 | Service Fee  | $14.12  |
 | Tax      | $16.05  |
 | Delivery Fee | $0.49   |
 | Tip      | $27.06  |
 | Special Offer | -$8.00  |

 ## Payments

 | Visa ····6451  | $262.65  |
 |-----------------|-----------|
 | 2/23/24 2:06 PM |      |
 | Visa ····6451  | $27.06  |
 | 2/23/24 3:06 PM |      |
 A> The original cost of the items ordered before any discounts was $247.99.


 36% 36/100 [04:01<07:33,  7.08s/it]INFO 2024-06-26 22:23:52,826 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What is the percentage of tax applied to bartaco orders, and what is the calculated tax amount for Luke's order?
 I> ## Thanks for tipping, Luke

 Here's your updated receipt for bartaco (Seaport).

 ...

 ## Tax      | $16.05  |

 ...

 ## Payments

 ...
 A> Bartaco charges a tax rate of 7.6% based on the shown receipt. The calculated tax amount for Luke's order is $16.05.

 Q> Was any tip given during the first payment, or was the first payment entirely service fee and subtotal?
 I> 
 A> The first payment of $262.65 includes a tip, service fee, and a part of the subtotal. No separate tip has been given during the first payment.


 38% 38/100 [04:11<06:33,  6.35s/it]INFO 2024-06-26 22:24:02,512 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Which special offer was applied to this receipt, and how much was saved through this offer?
 I> 
 A> A special offer of -$8.00, indicating an $8 savings, was applied to this receipt for bartaco (Seaport) as shown under 'Special Offer'.

 Q> Can you indicate what the sum of each category is on the receipt: subtotal, tip, service fee, tax, and delivery fee?
 I> 
 A> The sums in each category are as follows: Subtotal - $239.99, Tip - $27.06, Service Fee - $14.12, Tax - $16.05, and Delivery Fee - $0.49.


 40% 40/100 [04:21<05:51,  5.86s/it]INFO 2024-06-26 22:24:12,100 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Can you list the dishes ordered and their respective quantities?
 I> ## Receipt for Tony's Pizzeria

 | Item              | Quantity | Cost Each | Cost     |
 |------------------|----------|------------|-----------|
 | Meat Lovers Pizza| 1       | $15.95    | $15.95    |
 | Calzone           | 2       | $10.50    | $21.00    |
 | Greek Salad       | 1       | $5.95    | $5.95    |
 | Soft Drink         | 1       | $2.50    | $2.50    |
 A> Meat Lovers Pizza: 1, Calzone: 2, Greek Salad: 1, Soft Drink: 1.

 Q> Could you determine the total cost of a specific dish, such as "BBQ Pork Ribs"?
 I> ## Receipt for Jack's Barbecue

 | Item              | Quantity | Cost Each | Cost     |
 |------------------|----------|------------|-----------|
 | BBQ Pork Ribs    | 2       | $15.00    | $30.00    |
 | Grilled Chicken    | 1       | $12.00    | $12.00    |
 | Cornbread         | 1       | $3.50    | $3.50    |
 | Baked Beans       | 1       | $3.00    | $3.00    |
 A> $30.00 was the total cost of BBQ Pork Ribs.


 42% 42/100 [04:34<05:53,  6.10s/it]INFO 2024-06-26 22:24:25,390 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What was the total cost of the two margs from the receipt, including taxes?
 I> 
 A> $15.52 is the total cost for two margs as shown on the receipt, after adding sales tax.

 Q> What additional charges, if any, beyond the menu items and taxes appear on the receipt?
 I> 
 A> An optional gratuity of $5.00 and a parking fee of $6.00 have been added to the receipt outside of menu items and taxes.


 44% 44/100 [04:43<05:15,  5.64s/it]INFO 2024-06-26 22:24:34,586 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Determine the subtotal cost for each non-alcoholic beverage from the receipt.
 I> ## Thank you for dining at our restaurant!

 Below is your receipt for the [Rainbow Cafe](http://www.rainbowcafe.com/)

 ## Items Ordered

 | Item | **Quantity** | **Cost** |
 | --- | --- | --- |
 | Coke | 3 | $2.40 |
 | Sprite | 2 | $1.60 |
 | Iced Tea | 1 | $1.50 |
 | Espresso | 1 | $2.50 |
 A> The cost for each non-alcoholic beverage is as follows: Coke costs $2.40 (3 items), Sprite costs $1.60 (2 items), and Iced Tea has a cost of $1.50 (1 item). The Espresso doesn't fall under the non-alcoholic beverage category.

 Q> Summarize the tax and the total costs shown on the receipt.
 I> ## Here's the receipt for your meal today

   **Meal** | **Cost**
   --- | ---
   Seafood Pasta | $15.00
   Grilled Salmon | $19.50
   Caesar Salad | $6.34
   Iced Tea | $2.00
   
   **Tax**
   
   6% NJ Sales tax | $2.32

   **Total**

   Subtotal | $43.14
   Tax | $2.32
   Total | $45.46
 A> The tax amount on the receipt is $2.32 at a rate of 6%, while the total cost is $45.46, which includes the $43.14 subtotal and tax.


 46% 46/100 [04:55<05:11,  5.76s/it]INFO 2024-06-26 22:24:46,682 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Find the individual cost of an item from the receipt and mention its position in the list.
 I> ## Here's the receipt for your meal today

 ```bash
   **Item**              | **Cost**
   ---                  | ---
   Chicken Fried Steak   | $14.25
   Veggie Omelette      | $12.00
   Sausage Gravy        | $5.35
   Blueberry Pancakes   | $9.50
   Freshly Brewed Coffee| $2.25
   Biscuit              | $1.45
   Hash Browns          | $3.60
 ```
 A> The individual cost of the Veggie Omelette is $12.00, and it is the second item in the list.


 47% 47/100 [05:01<05:05,  5.76s/it]INFO 2024-06-26 22:24:52,420 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What was the total price of each item on the receipt, excluding tax and service fee?
 I> ## Thank You! Your Order Has Been Received

 ----------------------------------
 | Item | Quantity | Price |
 ----------------------------------
 | Hot Dog | 1 | $3.50 |
 | Curly Fries | 1 | $2.45 |
 | Soft Drink - 12oz | 2 | $4.50 |
 ----------------------------------
 A> * Hot Dog: $3.50
 * Curly Fries: $2.45
 * Soft Drink - 12oz: $4.50 x 2 = $9.00

 Q> Which item was the least expensive, and what was its unit price?
 I> <noinput>
 ## BILL OF LADING

 HBL: 79899000
 Vessel: A003 received on board on 24- Feb-23
 Port of Loading: SJDN
 Port of Discharge: STX

 Net Weight: 20117 lbs
 Gross Weight: 20117 lbs

 ## INVOICE
 ```makefile
 ITEM                 QTY   RATE  AMOUNT
 -------------------------------------------
 888-Abcd-1234      500    2.15    $1075
 9999-Bbbb-2233     320    2.78    $ 897.60
 123-Cccc-4567      700    1.45    $1015
 ```
 A> The least expensive item was 888-Abcd-1234 with a unit price of $2.15.


 49% 49/100 [05:13<04:55,  5.80s/it]INFO 2024-06-26 22:25:04,181 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 INFO 2024-06-26 22:25:05,910 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Deduce what service charge is applied in the given receipt and calculate its percentage.
 I> ## Fine Dining Restaurant Receipt

 | **Items** | **Quantity** | **Price Each** | **Cost** |
 | --- | --- | --- | --- |
 | Soup of the Day | 1 | $9.50 | $9.50 |
 | Grilled Chicken | 1 | $32.00 | $32.00 |
 | Dessert | 1 | $8.75 | $8.75 |
 | Coffee | 1 | $5.00 | $5.00 |
 | 15% Discretionary Service Charge | | | $8.75 |
 | **Subtotal** | | | $64.50 |
 | **Total** | | | **$73.25** |
 A> A discretionary service charge of 15% is applied, resulting in a $8.75 service charge. This forms 11.9% of the total bill.


 50% 50/100 [05:21<05:11,  6.24s/it]INFO 2024-06-26 22:25:12,236 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What was the date and time when Mexico City Cafe's receipt was generated?
 I> 
 A> The receipt from Mexico City Cafe was generated on July 1, 2022, at 8:15 PM.

 Q> For Suzy's order at the Simple Cafe, what is the price for each charged menu item?
 I> 
 A> Suzy was charged for the following menu items at Simple Cafe:
 * Avocado Toast: $11.00
 * Americano Coffee: $4.00
 * Quinoa Salad: $14.50


 52% 52/100 [05:30<04:30,  5.64s/it]INFO 2024-06-26 22:25:21,347 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What is the subtotal cost of the "Climbing Class Instructional Materials" on the receipt?
 I> ## Receipt: Mountaineering Academy

 ...

 ## Items

 | Item                  | Quantity | Unit Price | Line Total |
 |-----------------------|----------|------------|------------|
 | Climbing Class Instructional Materials | 1        | $50.00     | $50.00     |
 ...
 A> The subtotal cost of the 'Climbing Class Instructional Materials' is $50.00, as listed under Items on the receipt.

 Q> Calculate the total discount offered to the customer.
 I> ## Order Summary

 ...

 ## Discounts

 | Discount Name                 | Discount Amount |
 |--------------------------------|----------------|
 | Military Discount              | $15.00        |
 | Seniors' Day Discount          | $5.00         |
 A> The total discount offered to the customer is $20.00: $15.00 for Military Discount and $5.00 for Seniors' Day Discount.


 54% 54/100 [05:41<04:18,  5.63s/it]INFO 2024-06-26 22:25:32,579 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Which items on the receipt are subject to taxes, and what are their respective taxed amounts?
 I> ## Receipt for Home Depot

 | Item                                            | Quantity | Cost Each   | Cost        |
 |-------------------------------------------------|----------|--------------|-------------|
 | 15" Slip Fit Compression Support - 10-Pack        | 1       | $136.88      | $136.88    |
 | 1-1/2 in. Galv. Steel Threaded Rod, 72 in.           | 2       | $8.28       | $16.56    |
 | Mobile WiFi Hotspot - 10 GB (Verizon)             | 1       | $60.00      | $60.00    |
 | Pencil - Ticonderoga #2 Wood-Cased                    | 5       | $0.25       | $1.25     |
 | Stainless Steel Utility Bucket                      | 1       | $7.07       | $7.07     |
 | 3M ULTIMATE FUSION Bubble Gum Wrap                 | 1       | $10.99      | $10.99    |
 | Straight Pipe Cutter - 1-1/8 in.                     | 1       | $9.34       | $9.34     |
 | Acid Brush, 1 in.                  …                  | 1       | $2.19       | $2.19     |
 | Nestle Pure Life Water 16.9 fl. oz 24 Count         | 1       | $7.99       | $7.99     |
 A> The following items are subject to taxes:
 * 15" Slip Fit Compression Support - 10-Pack: $13.24
 * Mobile WiFi Hotspot - 10 GB (Verizon): $6.72
 * Stainless Steel Utility Bucket: $0.64

 The taxed amounts for each are:
 * Sales Tax: $20.60
 * Service Tax: $16.56

 Q> What is the sum of the cost of the items on the Chipotle receipt, excluding the taxes?
 I> ## Receipt for Chipotle

 | Item                         | Quantity | Cost Each| Cost     |
 |-------------------------------|----------|----------|-----------|
 | Chicken Burrito                  | 1       | $7.75    | $7.75    |
 | Chips & Guacamole              | 1       | $2.75    | $2.75    |
 | Soft Drink, 20oz -- Fountain        | 1       | $1.75    | $1.75    |
 A> The sum of the cost of the items on the Chipotle receipt, excluding the taxes, is $12.25.


 56% 56/100 [06:00<05:00,  6.83s/it]INFO 2024-06-26 22:25:51,200 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Subtotal, shipping, tax, and the total paid for the items in bartaco?
 I> 
 A> The subtotal of your bartaco order is $268.59, shipping is $0.00, and there is no tax. The total paid is $268.59.

 Q> Which meals from bartaco received positive feedback and why?
 I> Luke ordered 4 tacos, 1 arepa, 1 quesadilla; David ordered 3 tacos, 1 nachos; Abhishek ordered 1 tacos, 2 arepas, 1 guacamole & chips; Kate ordered 1 pork tamale, 1 salad, 1 taco; Nathan ordered 2 tacos; Kai ordered nothing; Aldo ordered 1 elotero, 1 quesadilla, 1 dessert; Shiv ordered nothing; Rameswar ordered 1 salad; Ruchir ordered 1 taco, 1 burger.
 A> * Most people seemed to enjoy their tacos; Luke had 4 tacos and provided positive feedback, David had 3 tacos and also left positive feedback, and Nathan with 2 tacos was likewise content with his meal. Abhishek appreciated the arepas. Aldo's elotero and dessert received good comments as well.


 58% 58/100 [06:11<04:28,  6.38s/it]INFO 2024-06-26 22:26:02,048 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Exactly how much was the service fee for the lunch order at Cafe Amici?
 I> ## Receipt for Cafe Amici

 | Item                    | Quantity | Cost Each    | Cost     |
 |--------------------------|----------|--------------|-----------|
 | Steak Sandwich           | 1       | $12.50     | $12.50   |
 | Caesar Salad              | 1       | $8.95 ~.~    | $8.95    |
 | Espresso (x2)            | 2       | $2.20 ~.~    | $4.40    |
 | Service fee               | <noinput> | <noinput>    | $10.00   |
 A> The exact service fee for a lunch order at Cafe Amici is $10.00.

 Q> What was the date of the H Mart grocery order, and what time was the delivery scheduled?
 I> ## Receipt for H Mart

 | Item                    | Quantity | Cost Each    | Cost     |
 |--------------------------|----------|--------------|-----------|
 | Pork Belly               | 1       | $5.25 ~.~    | $5.25    |
 | Seasoned Seaweed        | 3       | $2.69 ~.~    | $8.07    |
 | Kimchi                    | 2       | $3.75 ~.~    | $7.50    |
 | Delivery fee             | <noinput> | <noinput>    | $6.99    |
 | Ordered on               | 12/12/2022 | <noinput>    | <noinput>   |
 | Delivered at            | <noinput> | <noinput>    | 15:05    |
 A> The H Mart grocery order was placed on December 12, 2022, and it was scheduled to be delivered at 15:05.


 60% 60/100 [06:26<04:28,  6.71s/it]INFO 2024-06-26 22:26:16,918 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Identify the payment methods used and what was charged for each on the bartaco receipt.
 I> ## Thanks for tipping, Luke

 Here's your updated receipt for bartaco (Seaport).

 ... [payment section details omitted for brevity] ...
 A> Two payment methods were used: Visa 6451. The first transaction was $262.65, and the second was $27.06.

 Q> Is there any discount or promotional offer on the receipt? If so, specify its value.
 I> 
 A> Yes, there is a special offer on the receipt. It is for -$8.00.


 62% 62/100 [06:35<03:51,  6.09s/it]INFO 2024-06-26 22:26:26,336 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 INFO 2024-06-26 22:26:37,535 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 INFO 2024-06-26 22:26:40,312 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What are the subtotal, tax, and service charge?
 I> ```vbnet
  ## Receipt for Fancy Restaurant
 
  | Item    | Quantity | Cost Each   | Cost   |
  |---------|----------|--------------|--------|
  | Oysters|       2   | $3.45      | $6.90   |
  | Wine   |       1   | $50.00      | $50.00 |
  | Salmon   |     1   | $35.00     | $35.00 |
  | Dessert   |     1   | $10.00     | $10.00 |
 
  **Totals**
 
  Subtotal | $121.90 |
  Tax (10%)| $12.19 |
  Service Charge | $17.81 |
 
  **Grand Total** | $151.90|
 ```
 A> Subtotal is $121.90, tax is $12.19, and service charge is $17.81.

 Q> Have any discounts been applied, and if so, how much was the discount?
 I> <noinput>

 Receipt:
 ```vbnet
  ## Receipt for Target

  | Item         | Unit Price   | Quantity | Total   |
  |--------------|--------------|----------|---------|
  | Groceries     |      $50.00   |         1|   $50.00  |
  | electronics |     $200.00   |         2|   $400.00  |
  | Clothes      |      $100.00   |         1|   $100.00  |

  **Discount summaries**

  20% off first groceries purchase | Estimated Savings | $10.00
  50% off that toy set              | Estimated Savings | $25.00

  **Grand Total** | $535.00
 ```
 A> Yes, discounts have been applied. $10.00 for 20% off the first grocery purchase and $25.00 for 50% off a toy set.


 64% 64/100 [07:03<05:07,  8.53s/it]INFO 2024-06-26 22:26:54,477 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 INFO 2024-06-26 22:26:56,299 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 INFO 2024-06-26 22:26:57,594 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 INFO 2024-06-26 22:26:59,378 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Identify the least expensive item from the meal list.
 I> ## Here's the receipt for your meal today

   **Meal** | **Cost**
   --- | ---
   Seafood Pasta | $15.00
   Grilled Salmon | $19.50
   **Caesar Salad** | **$6.34**
   Iced Tea | $2.00
 A> The least expensive item at the meal is the Caesar Salad, priced at $6.34.

 Q> What was the total cost of each item and the tax combined?
 I> 
 A> * Seafood Pasta total cost is $16.30 including tax.
 * Grilled Salmon total cost is $20.73 including tax.
 * Caesar Salad total cost is $6.69 including tax.
 * Iced Tea total cost is $2.12 including tax.


 66% 66/100 [07:18<04:38,  8.18s/it]INFO 2024-06-26 22:27:09,228 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> How many people bought soft drinks, and what was the combined spending by those purchasers?
 I> ## Receipt:

 ## bartaco (Seaport)

 ## Subtotal: $239.99

 ## Service Fee: $14.12

 ## Tax: $16.05

 ## Delivery Fee: $0.49

 ## Tip: $27.06

 ## Items

 * Soft Drink - $4.50
 	+ 3x - Kai, Greg, Taylor
 * Fish Tacos - $13.25
 	+ 1x - Taylor
 * Chicken Tacos - $11.00
 	+ 1x - Luke
 * Guacamole - $8.50
 	+ 1x - Luke
 * Grilled Corn - $5.00
 	+ 1x - Kai
 * Margarita - $11.25
 	+ 1x - Greg

 ## Total: $289.71
 A> Three people bought soft drinks, and their combined spending was $13.50.

 Q> List the names of the people who spent more than $50 in total during their transaction with bartaco.
 I> 
 A> - Kai, Taylor, and Luke spent more than $50 during their transaction with bartaco.


 68% 68/100 [07:29<03:55,  7.36s/it]INFO 2024-06-26 22:27:20,144 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What is the total spend on cleaning supplies on the Target receipt?
 I> <noinput>

 Receipt:
 ```vbnet
  ## Receipt for Target

  ...

  | Item         | Unit Price   | Quantity | Total |
  |--------------|--------------|----------|-------|
  | W index      |      $1.99     |         1|   $1.99  |
  | Mop          |      $7.99     |         1|   $7.99  |
  | Dish soap    |      $5.89     |         1|   $5.89  |

  ...
 ```
 A> The total spend on cleaning supplies is $15.87 (including index, mop, and dish soap).

 Q> How much is the sales tax on electronics, and what is the subtotal for electronics in this receipt?
 I> <noinput>

 Receipt:
 ```vbnet
  ## Receipt for Target

  | Item      | Unit Price   | Quantity | Subtotal  |
  |-----------|--------------|----------|-----------|
  | Xbox      |      $250.25   |         1|   $250.25 |

  ...
 ```
 A> The sales tax on electronics is $12.51, and the subtotal for electronics is $250.25.


 70% 70/100 [07:41<03:28,  6.94s/it]INFO 2024-06-26 22:27:32,086 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 INFO 2024-06-26 22:27:42,527 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Calculate the total bill excluding tips and service charge for each person at the bartaco outing.
 I> <noinput>
 ```less
 | Name    | Item            | Each  | Qty  | Total  |
 |---------|-----------------|-------|------|--------|
 | Luke    | Food            | $     | 5.98 | $5.98  |
 | Luke    | Drink           | $     | 6.68 | $6.68  |
 | Luke    | Service Fee     | $     | 14.12| $14.12 |
 | David   | Margarita       | $7.99 | 1    | $7.99  |
 | David   | Service Charge  | $     | 2.00 | $2.00  |
 | Abhishek| Shrimp Tacos    | $6.99 | 1    | $6.99  |
 | David   | Service Fee     | $     | 10.45| $10.45 |
 | Kate    | Chicken Tacos   | $5.98 | 1    | $5.98  |
 | Nathan  | Pork Tacos     | $2.99 | 1    | $2.99  |
 | Kai     | Soft Drink      | $1.99 | 1    | $1.99  |
 | Aldo    | Sangria         | $3.99 | 1    | $3.99  |
 | Shiv    | Rice & Beans    | $3.99 | 1    | $3.99  |
 | Rameswar| Kale Salad      | $3.99 | 1    | $3.99  |
 | Ruchir  | Side Salad      | $2.99 | 1    | $2.99  |
 | Luke    | Service Fee     | $     | 3.5  | $3.5   |
 ```
 A> * Luke (You): $26.26
 * David: $19.98
 * Abhishek: $6.99
 * Kate: $5.98
 * Nathan: $2.99
 * Kai: $1.99
 * Aldo: $3.99
 * Shiv: $3.99
 * Rameswar: $3.99
 * Ruchir: $2.99

 Q> Who placed the orders with the least and the most count of orders?
 I> <noinput>
 ```yaml
 {
  "Luke": {
    "Food": 1,
    "Drink": 1
  },
  "Kai": {
    "Drink": 1
  },
  "David": {
    "Margarita": 1
  },
  "Abhishek": {
    "Shrimp Tacos": 1
  },
  "Kate": {
    "Chicken Tacos": 1
  },
  "Nathan": {
    "Pork Tacos": 1
  },
  "Rameswar": {
    "Kale Salad": 1
  },
  "Ruchir": {
    "Side Salad": 1
  },
  "Aldo": {
    "Sangria": 1
  },
  "Shiv": {
    "Rice & Beans": 1
  }
 }
 ```
 A> Luke and Kai both placed the least amount of orders with 2 orders. Ruchir placed the most count of orders with 1 order.


 72% 72/100 [08:07<04:07,  8.84s/it]INFO 2024-06-26 22:27:58,569 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What is the total cost of the order and the tax amount shown on the receipt?
 I> 
 A> * The total cost of the order is $52.99 and the tax amount is $4.39.

 Q> Was there any reward points or miles earned on the purchase receipt? If so, how many?
 I> 
 A> * Yes, there were reward points earned on the purchase receipt. 34 reward points were earned.


 74% 74/100 [08:16<03:14,  7.49s/it]INFO 2024-06-26 22:28:07,323 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Which payment method was used, and how much was paid with it?
 I> ## Receipt: Tibetan Kitchen

 ## Total

 ## $46.54

 | Subtotal | $39.00 |
 |-----------|--------|
 | Tip       | $1.50  |
 | Service Fee  | $3.48  |
 | Tax          | $2.56  |

 ## Payments

 | Visa ····6451 | $40.00 |
 |-----------------|--------|
 | Cash           | $6.54  |
 | 2/23/24 4:28 PM |       |
 A> On the receipt, 'Visa ····6451' was used for a payment of $40.00.

 Q> What amount was tipped, and what percentage of the subtotal did it represent?
 I> 
 A> The tip amount is not specified in the input information; hence, it cannot be determined. Therefore, it's not possible to establish its representation as a percentage of the subtotal.


 76% 76/100 [08:27<02:44,  6.83s/it]INFO 2024-06-26 22:28:17,912 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 INFO 2024-06-26 22:28:22,527 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> How much more was spent on the chicken tacos by Luke than the grilled corn by Kai?
 I> ## Receipt:

 ## bartaco (Seaport)

 ## Subtotal: $239.99

 ...

 ## Items

 * Chicken Tacos - $11.00
 	+ 1x - Luke
 * Grilled Corn - $5.00
 	+ 1x - Kai
 * ...

 ## Total: $289.71
 A> Luke spent $6 on chicken tacos more than what Kai spent on grilled corn.

 Q> Did each of the individuals—Greg, Taylor, and Kai—consume alcoholic beverages? If not, who is the exception?
 I> ## Receipt:

 ...

 ## Items

 * Soft Drink - $4.50
 	+ 3x - Kai, Greg, Taylor
 * Margarita - $11.25
 	+ 1x - Greg

 ...
 A> Only Greg consumed an alcoholic beverage. Kai and Taylor bought only soft drinks.


 78% 78/100 [08:41<02:34,  7.02s/it]INFO 2024-06-26 22:28:32,817 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Indicate the reason for the service fee charged at bartaco.
 I> > Your bartaco (Downtown) receipt is here.

 	## Total

 	## $200.43

 	| Subtotal   | $165.34  |
 	|---------------|-----------|
 	| Service Fee  | $13.56  |
 	| Tax      | $10.78  |
 	| Delivery Fee | $0.75   |
 	| Tip      | $10.00  |
 	| Special Offer | $0.00   |

 	## Payments

 	| Mastercard ····5189  | $185.34  |
 	|---------------------|-----------|
 	| 2/24/24 6:39 PM |      |
 A> The service fee at bartaco may cover costs related to staffing, maintenance, or other operational expenses. The specific reason for the $13.56 service fee may not be detailed on the receipt.

 Q> What was the total cost of the order, including tax, subtotal, and all fees and tips, from the provided receipt?
 I> ## Welcome to Freebirds! Here's your receipt.

 	## Total

 	## $31.67

 	| Subtotal   | $25.00  |
 	|---------------|-----------|
 	| **Chipotle**	 | $12.50  |
 	| Chicken Ench  | $12.50  |
 	| **Toppings**	 | $10.50  |
 	| **Handmade Chips**| $2.00   |
 	| **Drink**	 | $5.50   |
 	| **Large Drink**	 | $3.00  |
 	| --- | --- |
 	| Tax      | $3.83  |
 	| Delivery Fee | $1.50  |
 	| Tip      | $1.34  |
 	| --- | --- |
 	| **Payment**	 | **Cash**   |
 	| | **$31.67** |
 	| --- | --- |
 	| 2/15/24 11:05 AM |      |
 A> The total cost of the order was $31.67, including the tax of $3.83, subtotal of $25.00, and all fees and tips.


 80% 80/100 [08:56<02:21,  7.06s/it]INFO 2024-06-26 22:28:47,101 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> On the receipt, what is the tax rate for the Red Wine?
 I> ## Receipt: Classic Bistro

 ...

 ## Items

 | Item                  | Quantity | Unit Price | Line Total |
 |-----------------------|----------|------------|------------|
 | Red Wine               | 1        | $12.00     | $12.00     |
 ...
 A> The tax rate cannot be extracted directly from the entry of 'Red Wine'. However, if the tax rate is constant across all items, you may consider providing the tax rate for the entire receipt. Nonetheless, the specific tax rate for 'Red Wine' isn't stated on this line.

 Q> From the receipt, what should be crossed off the to-buy list?
 I> 
 A> You need to furnish a clear to-buy list to determine what could be crossed off based on the receipt. At present, only the items from a possible to-buy list along with their quantities and prices are visible, yet there isn't a to-buy list given.


 82% 82/100 [09:06<01:57,  6.56s/it]INFO 2024-06-26 22:28:57,872 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Who didn't contribute to the cost, according to the bill?
 I> ## Here's the bill from our dinner at La Fiesta (times 6)

 | Items | Units | Cost |
 | --- | --- | --- |
 | Fish Tacos | 1 | $9.50 |
 | Ceviche | 1 | $8.00 |
 | Burrito Bowl | 1 | $11.75 |
 | Churros | 1 | $4.50 |
 | Calamari | 1 | $7.00 |
 | G & T | 1 | $7.50 |

 | Name | Amount |
 | --- | --- |
 | James | $26.00 |
 | Emily | $0.00 |
 | Eric | $10.50 |
 | Brian | $15.00 |
 | Claire | $11.00 |
 A> Emily didn't contribute to the cost, according to the bill.


 83% 83/100 [09:13<01:50,  6.49s/it]INFO 2024-06-26 22:29:04,066 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 INFO 2024-06-26 22:29:05,662 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Using the following input, clarify whether the second 'Visa ····6451' payment of $27.06 is considered part of the overall tip.
 I> ## Thanks for tipping, Luke

 Here's your updated receipt for bartaco (Seaport).

 ...

 ## Service Fees

 Service fee 10% $23.99

 ...

 ## Payments

 | Visa ····6451  | $262.65  |
 |-----------------|-----------|
 | 2/23/24 2:06 PM |      |
 | Visa ····6451  | $27.06  |
 | 2/23/24 3:06 PM |      |
 A> No, the second 'Visa ····6451' payment of $27.06 is not considered part of the overall tip since it's specifically displayed under the 'Payments' section, separated from the 'Service Fees' section where the $18.89 tip is listed.


 84% 84/100 [09:21<01:50,  6.93s/it]INFO 2024-06-26 22:29:12,740 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Which restaurant provided the receipt for the vegetarian sushi order?
 I> ## Here is the receipt information:
 Le Pain Quotidien
 ---
 Items
 - Vegetarian Sushi, $16.50
 Subtotal: $16.50
 Tax: $1.54
 Total: **$18.04**
 A> Le Pain Quotidien provided the receipt for the vegetarian sushi order.

 Q> What is the quantity and unit price of tofu in the order summary?
 I> ## Order Summary from Zen Garden
 ...

 Items:
 - Pepper Tofu - $15.00 (Spicy peppers, Asian tofu, fresh vegetables, and oriental sauce)
 A> The quantity and unit price of tofu in the order summary are 1 (whole order), and $15.00.


 86% 86/100 [09:31<01:26,  6.18s/it]INFO 2024-06-26 22:29:22,491 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Find the time and date when the receipt was generated.
 I> ---
 <noinput>
 A> * The receipt was generated on 22nd June 2021 at 9:36 PM.

 Q> Sum up the food, alcohol, andtax subtotals for Mike's meal at Joe's.
 I> ---
 ----
 ----
 ```vbnet
 Joe's Bar & Restaurant

 Mike's Meal

 Subtotal
 ----------
 Food: $32.03
 Alcohol: $14.15
 Misc: $5.00
 Total: $51.18

 Tax: $4.93

 Total: $56.11
 ```
 ---
 A> The sum of the food, alcohol, and tax subtotals for Mike's meal at Joe's is $51.18.


 88% 88/100 [09:41<01:08,  5.73s/it]INFO 2024-06-26 22:29:32,226 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What was the cost before the applied discounts for the "toy set" item?
 I> ```vbnet
  ## Receipt for Target

  ...

  | Item         | Unit Price   | Quantity | Total   |
  |--------------|--------------|----------|---------|
  | Groceries     |      $50.00   |         1|   $50.00  |
  | electronics |     $200.00   |         2|   $400.00  |
  | Clothes      |      $100.00   |         1|   $100.00  |
  | toy set       |      $80.00    |         1|   $44.00   |

  **Discount summaries**
  ...

  **Grand Total** | $535.00
 ```
 A> The cost before the discount for the "toy set" was $80.00.

 Q> What is the category of the most expensive single item on the receipt?
 I> ```vbnet
  ## Receipt for Target

  ...

  | Item           | Unit Price | Quantity | Total    |
  |----------------|------------|----------|----------|
  | electronics    |   $150.00   |         1| $150.00  |
  | furniture set  |   $140.00   |         1| $140.00  |
  | ...
 ```
 A> The most expensive single item, "electronics", is from the 'electronics' category.


 90% 90/100 [09:53<00:59,  5.90s/it]INFO 2024-06-26 22:29:44,741 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Calculate the total cost of each drink type and the sum of all the ordered items shown in the receipt.
 I> ## Thank you for shopping at Local Liquor!

 Here's your receipt:

 ## Items Purchased

 | Item | Qty | Price per Item |
 | --- | --- | --- |
 | Absolut Vodka | 1 | $24.99 |
 | Red Bull | 3 | $1.65 |
 | Cointreau | 1 | $28.99 |
 | Cranberry Juice | 2 | $1.15 |
 A> The total cost for Absolut Vodka is $24.99, Red Bull costs $4.95 (3 items), Cointreau costs $28.99, and Cranberry Juice amounts to $2.30 (2 items). The sum of the ordered items equals $81.23 with tax included.

 Q> Identify which items from the receipt were ordered more than once by the same customer.
 I> 
 A> The Red Bull and Cranberry Juice were both ordered more than once. Specifically, Red Bull was ordered 3 times, and Cranberry Juice was ordered 2 times.


 92% 92/100 [10:04<00:45,  5.73s/it]INFO 2024-06-26 22:29:55,477 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Identify the name of the restaurant and the total cost of the order on the receipt.
 I> ## Receipt for Cafe Amici

 | Item                    | Quantity | Cost Each    | Cost     |
 |--------------------------|----------|--------------|-----------|
 | Steak Sandwich           | 1       | $12.50     | $12.50   |
 | Caesar Salad              | 1       | $8.95 ~.~    | $8.95    |
 | Espresso (x2)            | 2       | $2.20 ~.~    | $4.40    |
 | Service fee               | <noinput> | <noinput>    | $10.00   |
 A> The name of the restaurant is Cafe Amici and the total cost of the order is $35.85.

 Q> On the provided receipt, what items were ordered and how many of each?
 I> 
 A> * Steak Sandwich and Caesar Salad were ordered, with 1 quantity of each.
 * Two Espressos were also ordered.


 94% 94/100 [10:16<00:34,  5.73s/it]INFO 2024-06-26 22:30:06,953 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 INFO 2024-06-26 22:30:13,085 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What is the cost of each menu item ordered by the customer at Lucky Lobster Restaurant?
 I> ## Receipt for Lucky Lobster Restaurant

 | Item                    | Quantity | Cost Each | Cost     |
 |--------------------------|----------|------------|-----------|
 | Lobster Roll             | 2       | $13.95    | $27.90   |
 | Clam Strips             | 1       | $11.50    | $11.50   |
 | Chowder                | 1       | $8.50     | $8.50    |
 | Crab Cake                | 1       | $9.95     | $9.95    |
 A> * Lobster Roll cost $13.95 each
 * Clam Strips cost $11.50 each
 * Chowder cost $8.50 each
 * Crab Cake cost $9.95 each

 Q> What is the exact amount both Amelia and Jessica have paid for their meals at Sushi House?
 I> ## Receipt for Sushi House

 | Diner       | Item                    | Quantity | Cost Each | Cost     |
 |--------------|--------------------------|----------|------------|-----------|
 | Amelia       | Yellowtail Roll         | 3       | $7.95     | $23.85   |
 | Amelia       | Spicy Tuna Roll         | 2       | $6.95     | $13.90   |
 | Jessica       | Salmon Roll            | 2       | $6.95     | $13.90   |
 | Jessica       | California Roll         | 1       | $4.95     | $4.95    |
 A> Amelia paid $37.75, and Jessica paid $18.85 for their meals at Sushi House.


 96% 96/100 [10:36<00:28,  7.16s/it]INFO 2024-06-26 22:30:27,632 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 INFO 2024-06-26 22:30:43,636 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> What is the final amount spent at Home Depot, including tax?
 I> ## Receipt
 ---

 | **Home Depot receipt** |
 | --- |
 | March 4, 2022 |
 | Receipt #: 31699042 |
 | Cashier: Logan H. |
 | --- |
 | **Item** | **Price (per unit)** | **Quantity** | **Subtotal** |
 | --- | --- | --- | --- |
 | DEWALT 20V MAX XR Brushless Hammer Drill/Driver | $199.00 | 1 | $199.00 |
 | DEWALT FLEXVOLT 60V MAX Lithium-Ion Cordless Table Saw | $599.00 | 1 | $599.00 |
 | Makita 18V Lithium-Ion Cordless 2-Piece Combo Kit (Drive Drill and Impact Driver) | $179.00 | 1 | $179.00 |
 | Bosch Router Tool | $149.00 | 1 | $149.00 |
 | 6 pack of Milwaukee 18-Volt XC5.0 Batteries | $235.00 | 1 | $235.00 |
 | --- | --- | --- | --- |
 | **Subtotal:** | **$1,361.00** | | |
 | **Tax (9.25%):** | **$124.68** | | |
 | **Total:** | **$1,485.68** | | |
 ---
 A> * The final amount spent at Home Depot was $1,485.68, including tax.

 Q> On the Staples receipt, which item has a discount applied to it?
 I> ## Receipt

 ---

 | **Staples Receipt** |
 | --- |
 | February 14, 2022 |
 | Receipt #: 31698222 |
 | Cashier: John D. |
 | --- |
 | **Item** | **Price (per unit)** | **Quantity** | **Subtotal** | **Discount** |
 | --- | --- | --- | --- | --- |
 | Brother HL-L2350DW Monochrome Laser Printer | $199.99 | 1 | $199.99 | |
 | Canon PIXMA TR4520 Series All-In-One Printer | $79.99 | 1 | $79.99 | |
 | Logitech MX Anywhere 2S Wireless Mouse | $49.99 | 1 | $49.99 | 15% Off |
 | HP 24mh FHD Monitor | $169.99 | 1 | $169.99 | |
 | Brother TN-420 Drum Kit for MFC-L8900CDW Monochrome Laser All-in-One | $89.99 | 1 | $89.99 | |
 | --- | --- | --- | --- | --- |
 | **Subtotal:** | **$589.95** | | | |
 | **Discount:** | **-$7.50** | | | |
 | **Tax (7.25%):** | **$43.56** | | | |
 | **Total:** | **$575.99** | | | |
 ---
 A> * The Logitech MX Anywhere 2S Wireless Mouse has a discount applied to it.


 98% 98/100 [11:09<00:19,  9.91s/it]INFO 2024-06-26 22:30:59,881 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> List all the items purchased at the grocery store, along with their quantities.
 I> ## Grocery Store Receipt

 ------------------------

 | **Item Name** | **Price (per unit)** | **Quantity** | **Subtotal** |

 | --- | --- | --- | --- |

 | Avocados | $0.99 | 6 | $5.94 |

 | Bananas | $0.39 | 12 | $4.68 |

 | Sour Cream | $2.79 | 1 | $2.79 |

 | San Marzano Tomatoes | $6.99 | 2 | $13.98 |

 | Tortilla Chips | $4.59 | 1 | $4.59 |

 | Vegan Chocolate Chip Cookies | $3.49 | 1 | $3.49 |

 | ------------------------ |  |  |  |

 | **Subtotal:** | | | **$31.47** |

 | **Tax (8.25%):** | | | **$2.58** |

 | **Total:** | | | **$34.05** |

 -------------------------
 A> The items purchased at the grocery store along with their quantities are:

 * Avocados (6)
 * Bananas (12)
 * Sour Cream (1)
 * San Marzano Tomatoes (2)
 * Tortilla Chips (1)
 * Vegan Chocolate Chip Cookies (1)

 ** Total

 * $34.05


 99% 99/100 [11:16<00:09,  9.50s/it]INFO 2024-06-26 22:31:07,532 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->receipt->reasoning
 Q> Based on the bartaco receipt, what was the cost of the tuna tartare, and what was the price of the baja fish tacos?
 I> ## bartaco Receipt

 | Item                    | Quantity | Cost Each    | Cost     |
 |--------------------------|----------|--------------|-----------|
 | Tuna Tartare            | 1       | $15.00 ~.~   | $15.00    |
 | Baja Fish Tacos          | 2       | $6.00 ~.~    | $12.00    |
 | Chicken Burrito          | 1       | $14.00 ~.~   | $14.00    |
 | Watermelon Margarita     | 1       | $9.00 ~.~    | $9.00    |
 A> The cost of the tuna tartare at bartaco was $15.00, and the baja fish tacos cost $6.00 each, for a total of $12.00.


 100% 100/100 [11:23<00:00,  9.04s/it]
 100% 100/100 [11:23<00:00,  6.84s/it]
 INFO 2024-06-26 22:31:14,778 generate_data.py:609: generate_data 100 instructions generated, 25 discarded due to format (see /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/receipt/reasoning/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T22_19_50.log), 0 discarded due to rouge score
 INFO 2024-06-26 22:31:14,778 generate_data.py:613: generate_data Generation took 683.98s
 Completed 79.2 KiB/200.6 KiB (545.8 KiB/s) with 4 file(s) remaining
 upload: ../outputtopush/train_Mixtral-8x7B-Instruct-v0_2024-06-26T22_19_50.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/receipt/reasoning/train_Mixtral-8x7B-Instruct-v0_2024-06-26T22_19_50.jsonl
 Completed 79.2 KiB/200.6 KiB (545.8 KiB/s) with 3 file(s) remaining
 Completed 174.7 KiB/200.6 KiB (1.1 MiB/s) with 3 file(s) remaining 
 upload: ../outputtopush/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T22_19_50.json to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/receipt/reasoning/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T22_19_50.json
 Completed 174.7 KiB/200.6 KiB (1.1 MiB/s) with 2 file(s) remaining
 Completed 177.6 KiB/200.6 KiB (753.6 KiB/s) with 2 file(s) remaining
 upload: ../outputtopush/test_Mixtral-8x7B-Instruct-v0_2024-06-26T22_19_50.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/receipt/reasoning/test_Mixtral-8x7B-Instruct-v0_2024-06-26T22_19_50.jsonl
 Completed 177.6 KiB/200.6 KiB (753.6 KiB/s) with 1 file(s) remaining
 Completed 200.6 KiB/200.6 KiB (722.0 KiB/s) with 1 file(s) remaining
 upload: ../outputtopush/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T22_19_50.log to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/receipt/reasoning/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T22_19_50.log
 compositional_skills/extraction/information/named_entities/places/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/extraction/information/named_entities/places/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/information/named_entities/places --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T22:31:17Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/extraction/information/named_entities/places/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 22:31:25,391 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->information->named_entities->places
 [31mGenerating dataset failed with the following error: There was a problem with the new data, please make sure the yaml is formatted correctly, and there is enough new data(2+ Q&A))[0m

  0% 0/100 [00:00<?, ?it/s]
 compositional_skills/extraction/abstractive/abstract/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/extraction/abstractive/abstract/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/abstractive/abstract --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T22:31:26Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/extraction/abstractive/abstract/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.
 Error: An example in the taxonomy path compositional_skills->extraction->abstractive->abstract is too long for the server context size of 4096. Ensure the total number of characters across the combined question, answer, and context is less than 4896 for each example or use a server with a larger context size.
 compositional_skills/extraction/invoice/plain_text/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/extraction/invoice/plain_text/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/invoice/plain_text --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T22:31:35Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/extraction/invoice/plain_text/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 22:31:43,961 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text

  0% 0/100 [00:07<?, ?it/s]INFO 2024-06-26 22:31:51,271 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Can you compute the subtotal of the invoice?
 I> 
 A> 53,964.99

 Q> What are the details of the items ordered?
 I> ## INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 ## PURCHASED BY:

 John Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789 Phone: 111-222-3333

 ## COMMENTS OR SPECIAL INSTRUCTIONS:

 Due upon receipt

 | QUANTITY  | DESCRIPTION         | UNIT PRICE      | TOTAL   |
 |------------|------------------------------|-----------------------|-----------|
 | 1 TB    | Cloud service        | 99.99         | 99.99   |
 | 27     | Odyssey Ark 55-inch Monitors | 1,952         | 52,704  |
 | 27     | Standard Keyboards      | 32          | 864    |
 | 27     | Standard Mice        | 11          | 297    |
 | 27     |               |            |      |
 | 27     |               | Subtotal       | 53,964.99 |
 | 27     |               | Sales tax       | 3,237.90 |
 | 27     |               | Shipping and handling | 0.00   |
 | 27     |               | TOTAL DUE       | 57,202.89 |

 INVOICE # 21

 DATE: 2/21/2024

 SHIP TO:

 Jane Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, Nj 56789

 Phone: 111-222-3333
 A> - 1 TB Cloud service, 99.99 per unit
 - 27 Odyssey Ark 55-inch Monitors, 1,952 per unit
 - 27 Standard Keyboards, 32 per unit
 - 27 Standard Mice, 11 per unit


  2% 2/100 [00:22<12:36,  7.71s/it]INFO 2024-06-26 22:32:06,700 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the total due on the invoice?
 I> ## INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 ## PURCHASED BY:

 John Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789 Phone: 111-222-3333

 ## COMMENTS OR SPECIAL INSTRUCTIONS:

 Due upon receipt

 | QUANTITY  | DESCRIPTION         | UNIT PRICE      | TOTAL   |
 |------------|------------------------------|-----------------------|-----------|
 | 1 TB    | Cloud service        | 99.99         | 99.99   |
 | 27     | Odyssey Ark 55-inch Monitors | 1,952         | 52,704  |
 | 27     | Standard Keyboards      | 32          | 864    |
 | 27     | Standard Mice        | 11          | 297    |
 | 27     |               |            |      |
 | 27     |               | Subtotal       | 53,964.99 |
 | 27      |               | Sales tax       | 3,237.90 |
 | 27     |               | Shipping and handling | 0.00   |
 | 27     |               | TOTAL DUE       | 57,202.89 |

 INVOICE # 21

 DATE: 2/21/2024

 SHIP TO:

 Jane Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, Nj 56789

 Phone: 111-222-3333
 A> 57,202.89

 Q> Who is the invoice shipped to?
 I> ## INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 ## PURCHASED BY:

 John Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789 Phone: 111-222-3333

 ## COMMENTS OR SPECIAL INSTRUCTIONS:

 Due upon receipt

 | QUANTITY  | DESCRIPTION         | UNIT PRICE      | TOTAL   |
 |------------|------------------------------|-----------------------|-----------|
 | 1 TB    | Cloud service        | 99.99         | 99.99   |
 | 27     | Odyssey Ark 55-inch Monitors | 1,952         | 52,704  |
 | 27     | Standard Keyboards      | 32          | 864    |
 | 27     | Standard Mice        | 11          | 297    |
 | 27     |               |            |      |
 | 27     |               | Subtotal       | 53,964.99 |
 | 27     |               | Sales tax       | 3,237.90 |
 | 27     |               | Shipping and handling | 0.00   |
 | 27     |               | TOTAL DUE       | 57,202.89 |

 INVOICE # 21

 DATE: 2/21/2024

 SHIP TO:

 Jane Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, Nj 56789

 Phone: 111-222-3333
 A> Jane Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789


  4% 4/100 [00:44<15:14,  9.53s/it]INFO 2024-06-26 22:32:28,296 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Which items have the highest and lowest unit price respectively?
 I> ## INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 ## PURCHASED BY:

 John Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789 Phone: 111-222-3333

 ## COMMENTS OR SPECIAL INSTRUCTIONS:

 Due upon receipt

 | QUANTITY  | DESCRIPTION         | UNIT PRICE      | TOTAL   |
 |------------|------------------------------|-----------------------|-----------|
 | 1 TB    | Cloud service        | 99.99         | 99.99   |
 | 27     | Odyssey Ark 55-inch Monitors | 1,952         | 52,704  |
 | 27     | Standard Keyboards      | 32          | 864    |
 | 27     | Standard Mice        | 11          | 297    |
 | 27     |               |            |      |
 | 27     |               | Subtotal       | 53,964.99 |
 | 27     |               | Sales tax       | 3,237.90 |
 | 27     |               | Shipping and handling | 0.00   |
 | 27     |               | TOTAL DUE       | 57,202.89 |

 INVOICE # 21

 DATE: 2/21/2024

 SHIP TO:

 Jane Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, Nj 56789

 Phone: 111-222-3333
 A> The item with the lowest unit price is the Cloud service with a unit price of 99.99 and the item with the highest unit price is the Odyssey Ark 55-inch Monitors with a unit price of 1,952.

 Q> What is the sales tax charged on the invoice?
 I> 
 A> The sales tax charged on the invoice is 3,237.90.


  6% 6/100 [00:59<13:37,  8.69s/it]INFO 2024-06-26 22:32:43,696 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the total amount due from the invoice?
 I> 
 A> 57,202.89

 Q> Which customer is this invoice sent to?
 I> ## INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 SHIP TO:

 John Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, Nj 56789

 Phone: 111-222-3333
 A> The invoice is sent to John Doe at J&J corp in the address of 777 77 $^{th}$ st, Newark, NJ 56789.


  8% 8/100 [01:09<11:01,  7.20s/it]INFO 2024-06-26 22:32:53,492 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What date is indicated for the payment due?
 I> ## INVOICE

 INVOICE No.: INV-00025

 ISSUED: March 15, 2023

 DUE DATE: March 29, 2023

 TOTAL: $12,500.00

 Bill To:
 Acme Inc.

 Mr. John Smith
 123 Park Ave
 New York, NY 10001
 A> The payment due date for this invoice is March 29, 2023.

 Q> What is the current balance after the invoice is applied?
 I> | Customer | Due Date | Due Amount | Balance |
 | --- | --- | --- | --- |
 | ABC Inc. | 2023-02-28 | $5,231.00 | $13,489.00 |
 |  | 2023-03-31 | $8,675.00 | $18,783.89 |
 | XYZ Corp. | 2023-03-15 | $34,137.00 | $56,784.89 |
 |  | 2023-04-14 | $22,000.00 | $74,492.94 |
 A> For the customer ABC Inc., the balance becomes $21,120.89 after the new invoice is applied while the customer XYZ Corp. reaches a balance of $106,489.89.


 10% 10/100 [01:21<10:05,  6.72s/it]INFO 2024-06-26 22:33:05,265 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the date of the oldest outstanding invoice?
 I> | Customer | Due Date | Due Amount | Balance |
 | --- | --- | --- | --- |
 | ABC Inc. | 2023-02-28 | $5,231.00 | $13,489.00 |
 |  | 2023-03-31 | $8,675.00 | $18,783.89 |
 | XYZ Corp. | 2023-03-15 | $34,137.00 | $56,784.89 |
 |  | 2023-04-14 | $22,000.00 | $74,492.94 |
 A> The oldest outstanding invoice is due on 2023-03-15.

 Q> Who should the invoice be shipped to?
 I> INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 ## PURCHASED BY:

 John Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789 Phone: 111-222-3333

 ## SHIP TO:

 Jane Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789 Phone: 111-222-3333

 COMMENTS OR SPECIAL INSTRUCTIONS:

 Due upon receipt

 | QUANTITY  | DESCRIPTION         | UNIT PRICE      | TOTAL   |
 |------------|------------------------------|-----------------------|-----------|
 | 1 TB    | Cloud service        | 99.99         | 99.99   |
 | 27     | Odyssey Ark 55-inch Monitors | 1,952         | 52,704  |
 | 27     | Standard Keyboards      | 32          | 864    |
 | 27     | Standard Mice        | 11          | 297    |
 | 27     |               |            |      |
 | 27     |               | Subtotal       | 53,964.99 |
 | 27     |               | Sales tax       | 3,237.90 |
 | 27     |               | Shipping and handling | 0.00   |
 | 27     |               | TOTAL DUE       | 57,202.89 |

 INVOICE # 21

 DATE: 2/21/2024
 A> The invoice should be shipped to Jane Doe at 777 77th Street, Newark, NJ 56789.


 12% 12/100 [01:38<10:43,  7.31s/it]INFO 2024-06-26 22:33:22,163 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the subtotal of the order?
 I> # INVOICE
 888 Park Ave San Diego, CA 92101 Phone: 555-123-4567
 PURCHASED BY:
 Helen Taylor Johnson Inc. 88 Pine St San Francisco, CA 94111 Phone: 555-543-2110
 COMMENTS OR SPECIAL INSTRUCTIONS:
 Pre-tax only, due in 15 days
 ITEMS:
 QTY DESCRIPTION UNIT PRICE TOTAL
 10 HD Security Cameras $200.00 $2,000.00
 50 Surge Protectors $12.50 $625.00
 25 1TB External Hard Drives $79.99 $1,999.75
 ITEMS SUBTOTAL $4,624.75
 TAXES APPLICABLE 7.5% $346.86
 TOTAL DUE $4,971.61
 INVOICE # 22
 DATE: 5/12/2023
 SHIP TO:
 Helen Taylor
 Johnson Inc.
 88 Pine St
 San Francisco, CA 94111
 Phone: 555-543-2110
 A> The subtotal of the order is $4,624.75.

 Q> Who is the order shipped to?
 I> INVOICE
 456 Maple St Denver, CO 80202 Phone: 555-987-6543
 PURCHASED BY:
 Hannah Rogers Acme Inc. 123 Elm St New York, NY 10001 Phone: 555-111-2222
 COMMENTS OR SPECIAL INSTRUCTIONS:
 Prepaid shipping
 ITEMS:
 QTY DESCRIPTION UNIT PRICE TOTAL
 10 Projectors $350.00 $3,500.00
 20 Laser Pointer $15.00 $300.00
 ITEMS SUBTOTAL $3,800.00
 TAXES APPLICABLE 8.25% $314.50
 TOTAL DUE $4,114.50
 INVOICE # 23
 DATE: 6/3/2023
 SHIP TO:
 Hannah Rogers
 Acme Inc.
 123 Elm St
 New York, NY 10001
 Phone: 555-111-2222
 A> The order is shipped to Hannah Rogers at Acme Inc. at 123 Elm St, New York, NY 10001.


 14% 14/100 [01:52<10:25,  7.27s/it]INFO 2024-06-26 22:33:36,549 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Explain the next step to approve this invoice.
 I> INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 ## PURCHASED BY:

 John Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789 Phone: 111-222-3333

 ## SHIP TO:

 Jane Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789 Phone: 111-222-3333

 COMMENTS OR SPECIAL INSTRUCTIONS:

 Please review and approve the invoice for payment.

 | QUANTITY  | DESCRIPTION         | UNIT PRICE      | TOTAL   |
 |------------|------------------------------|-----------------------|-----------|
 | 1 TB    | Cloud service        | 99.99         | 99.99   |
 | 27     | Odyssey Ark 55-inch Monitors | 1,952         | 52,704  |
 | 27     | Standard Keyboards      | 32          | 864    |
 | 27     | Standard Mice        | 11          | 297    |
 | 27     |               |            |      |
 | 27     |               | Subtotal       | 53,964.99 |
 | 27     |               | Sales tax       | 3,237.90 |
 | 27     |               | Shipping and handling | 0.00   |
 | 27     |               | TOTAL DUE       | 57,202.89 |

 INVOICE # 21

 DATE: 2/21/2024
 A> To approve this invoice, the next step is to review the invoice and authorize the payment of $57,202.89.

 Q> What is the total cost of the invoice?
 I> 
 A> The total cost of the invoice can be determined by adding up all the charges for goods or services and any additional fees such as shipping, handling, and taxes. The total due is indicated at the bottom of the invoice.


 16% 16/100 [02:08<10:24,  7.43s/it]INFO 2024-06-26 22:33:52,092 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What are the details of the purchases made?
 I> 
 A> The purchase details can be found in the "QUANTITY," "DESCRIPTION," and "UNIT PRICE" columns. This information includes the number of items, the description, and the unit price for each item.

 Q> Who is the invoice being sent to for payment?
 I> 
 A> The invoice is being sent to J&J corp, located at 777 77 $^{th}$ st Newark, NJ 56789. They can be reached at Phone: 111-222-3333.


 18% 18/100 [02:17<08:58,  6.56s/it]INFO 2024-06-26 22:34:01,404 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 INFO 2024-06-26 22:34:05,594 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Which items were purchased and in what quantities?
 I> INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 ## PURCHASED BY:

 John Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789 Phone: 111-222-3333

 ## SHIP TO:

 Jane Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789 Phone: 111-222-3333

 COMMENTS OR SPECIAL INSTRUCTIONS:

 Due upon receipt

 | QUANTITY  | DESCRIPTION         | UNIT PRICE      | TOTAL   |
 |------------|------------------------------|-----------------------|-----------|
 | 1 TB    | Cloud service        | 99.99         | 99.99   |
 | 27     | Odyssey Ark 55-inch Monitors | 1,952         | 52,704  |
 | 27     | Standard Keyboards      | 32          | 864    |
 | 27     | Standard Mice        | 11          | 297    |

 INVOICE # 21

 DATE: 2/21/2024
 A> The items purchased are: 1 TB Cloud service, 27 Odyssey Ark 55-inch monitors, 27 Standard Keyboards, and 27 Standard Mice.


 19% 19/100 [02:30<10:25,  7.72s/it]INFO 2024-06-26 22:34:14,307 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Detail the purchases made by John Doe.
 I> 
 A> John Doe purchased the following:
 - 1 TB Cloud service at a unit price of 99.99 dollars.
 - 27 Odyssey Ark 55-inch Monitors.
 - 27 Standard Keyboards.
 - 27 Standard Mice.

 Q> List the units purchased with their respective prices.
 I> ## INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 ## PURCHASED BY:

 John Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789 Phone: 111-222-3333

 ... (rest of the invoice text)
 A> - 1 TB at 99.99 dollars.
 - 27 Odyssey Ark 55-inch Monitors at 1,952 dollars each.
 - 27 Standard Keyboards at 32 dollars each.
 - 27 Standard Mice at 11 dollars each.


 21% 21/100 [02:40<09:04,  6.89s/it]INFO 2024-06-26 22:34:24,916 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the amount past due for a given invoice?
 I> | Customer | Due Date | Due Amount | Balance |
 | --- | --- | --- | --- |
 | ABC Inc. | 2023-02-28 | $5,231.00 | $13,489.00 |
 |  | 2023-03-31 | $8,675.00 | $18,783.89 |
 | XYZ Corp. | 2023-03-15 | $34,137.00 | $56,784.89 |
 |  | 2023-04-14 | $22,000.00 | $74,492.94 |
 A> For invoice ABC Inc. on 2023-03-31, the past due amount is $10,514.89.

 Q> Explain the payment terms for a given invoice.
 I> ```vbnet
 INVOICE # 21

 DATE: 2/21/2024

 SHIP TO:

 Jane Doe
 J&J corp
 777 77 7th st
 Newark, NJ 56789
 Phone: 111-222-3333

 PAY TO:

 Jane Doe
 J&J corp
 222 22 2nd Ave
 Boston, MA 01234
 Phone: 123-123-1234

 TERMS: Net 30

 ITEMS:

 # | Quantity | Description | Unit Cost | Total
 ----------------------------------------------------
 1 | 27 | Odyssey Ark 55-inch Monitors | $1,952.00 | $52,704.00
 2 | 27 | Standard Keyboards | $32.00 | $864.00
 3 | 27 | Standard Mice | $11.00 | $297.00
 4 | 1 TB | Cloud Service | $99.99 | $99.99
 TOTAL: | $53,964.99
 TAX: | $3,237.90
 SHIPPING: | $0.00
 TOTAL DUE: | $57,202.89

 Signed: ___________
 ```
 A> The payment terms for this invoice are Net 30, meaning the full amount is due within 30 days.


 23% 23/100 [02:54<08:52,  6.91s/it]INFO 2024-06-26 22:34:38,823 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Identify the purchase order number of this invoice.
 I> INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 ## PURCHASED BY:

 John Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789 Phone: 111-222-3333

 ## COMMENTS OR SPECIAL INSTRUCTIONS:

 Due upon receipt

 | QUANTITY  | DESCRIPTION         | UNIT PRICE      | TOTAL   |
 |------------|------------------------------|-----------------------|-----------|
 | 1 TB    | Cloud service        | 99.99         | 99.99   |
 | 27     | Odyssey Ark 55-inch Monitors | 1,952         | 52,704  |
 | 27     | Standard Keyboards      | 32          | 864    |
 | 27     | Standard Mice        | 11          | 297    |
 | 27     |               |            |      |
 | 27     |               | Subtotal       | 53,964.99 |
 | 27     |               | Sales tax       | 3,237.90 |
 | 27     |               | Shipping and handling | 0.00   |
 | 27     |               | TOTAL DUE       | 57,202.89 |

 INVOICE # 21

 DATE: 2/21/2024

 PO #: **123456**

 SHIP TO:

 Jane Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, Nj 56789

 Phone: 111-222-3333
 A> The purchase order number is 123456.

 Q> What is the total amount of taxes indicated in the invoice?
 I> INVOICE

 555 5 $^{th}$ st

 Boston, MA 01234

 Phone: 123-456-7890

 PURCHASED BY:

 John Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, NJ 56789

 Phone: 111-222-3333

 Comments or Special Instructions:

 Due upon receipt

 | QUANTITY  | DESCRIPTION    | UNIT PRICE  | TOTAL   |
 |------------|-----------------------------|-------------|----------|
 | 2         | abc             , xyz | $200.00   | $400.00 |
 | 1          | Mno             , pqr | 2000.00   | 2000.00 |
 | 3          | stu             , vwx | 500.00    | 1500.00 |

 Ship To:

 Joan Smith

 TUV Business Solutions

 123 Any Street

 New York, NY 00111

 Invoice Number: 00458

 Date: 04/14/2021

 Shipping and Handling: $100.00

 TAX RATE: 8%
 A> The total amount of taxes indicated in the invoice is $240.00.


 25% 25/100 [03:14<09:43,  7.78s/it]INFO 2024-06-26 22:34:58,108 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the due date for this invoice?
 I> ## INVOICE
 [...]
 A> The invoice is due on 2/21/2024.

 Q> What is the sales tax for this order?
 I> ## INVOICE
 [...]
 A> The sales tax for this order is $3,237.90.


 27% 27/100 [03:22<08:08,  6.69s/it]INFO 2024-06-26 22:35:06,680 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What are the due amounts for all customers as of the current date?
 I> | Customer | Due Date | Due Amount | Balance |
 | --- | --- | --- | --- |
 | ABC Inc. | 2023-02-28 | $5,231.00 | $13,489.00 |
 |  | 2023-03-31 | $8,675.00 | $18,783.89 |
 | XYZ Corp. | 2023-03-15 | $34,137.00 | $56,784.89 |
 |  | 2023-04-14 | $22,000.00 | $74,492.94 |
 A> The due amounts for ABC Inc. are $5,231.00 and $8,675.00, while the due amounts for XYZ Corp. are $34,137.00 and $22,000.00.

 Q> What is the ship-to information for this invoice?
 I> INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 PO# 456789

 PURCHASED BY:

 John Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, Nj 56789

 Phone: 111-222-3333

 ITEMS:

 1 TB Cloud service $^{99.99}$/each

 5 @ $55.31 each

 SHIP VIA:

 UPS Ground Shipping

 SHIP TO:

 Jane Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, Nj 56789

 Phone: 111-222-3333

 Tax: $46.58
 A> The ship-to information for this invoice is Jane Doe, J&J corp, 777 77th st, Newark, NJ 56789, Phone: 111-222-3333


 29% 29/100 [03:36<07:55,  6.70s/it]INFO 2024-06-26 22:35:20,124 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the total amount that needs to be paid by Jane Doe?
 I> INVOICE
 [...]
 SHIP TO:
 Jane Doe
 J&J corp
 777 77 $^{th}$ st
 Newark, NJ 56789
 Phone: 111-222-3333
 ** Total Due: $57,202.89
 A> The total amount that needs to be paid by Jane Doe is $57,202.89.

 Q> Which invoice number is associated with this email?
 I> INVOICE
 [...]
 INVOICE # 21
 A> The invoice number associated with this email is 21.


 31% 31/100 [03:45<07:00,  6.09s/it]INFO 2024-06-26 22:35:29,540 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the contact information of the purchaser?
 I> ## INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 ## PURCHASED BY:

 John Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789 Phone: 111-222-3333

 ... (rest of the invoice text)
 A> John Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789 Phone: 111-222-3333

 Q> What are the products or services included in the invoice?
 I> ## INVOICE

 [...]
 A> - 1 TB of storage
 - 27 Odyssey Ark 55-inch Monitors
 - 27 Standard Keyboards
 - 27 Standard Mice


 33% 33/100 [03:55<06:26,  5.77s/it]INFO 2024-06-26 22:35:39,644 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 INFO 2024-06-26 22:35:45,013 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 INFO 2024-06-26 22:35:51,011 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Identify the shipping address specified in the invoice.
 I> INVOICE 687-D2-2103

 INVOICED TO:

 Acme Corp

 555 Fake Rd

 Cityville, NY 12345

 Terms: NET 30

 DATE: 03/05/2021

 ITEM(S):

 Item #: ABC123 Rev: 02

 Description: Electro-Magnetic Damper

 Quantity: 1

 Item #: DEF456 Rev: 01

 Description: Green Energy Ultra Cells

 Quantity: 2

 Item #: GHI789 Rev: 05

 Description: Long-range Sensor Units

 Quantity: 1

 SHIPPED TO:

 Acme Corp TEST LAB

 123 Test Way

 Cityville, NY 12345

 Terms: Net 30

 Freight: UPS Ground

 Ship Date: 03/08/2021
 A> The shipping address specified in the invoice is Acme Corp TEST LAB, 123 Test Way, Cityville, NY 12345.

 Q> What is the unit cost of item DEF456 in the invoice?
 I> INVOICE # 003

 DATE 10/7/2020

 ITINERARY

 Territory: New York

 Territory Manager: Robert John

 SALES EXECUTIVE

 Account Name: John Doe

 Account Name: Janet Doe

 INVOICE

 Bill To:

 John Doe

 C/O XYZ Industries

 950 3rd Avenue

 New York, NY 10022

 Items:

 Code Item Name Unit Cost Quantity Total Cost
 01 ACME Water Pump $540.00 1 $540.00
 02 ACME Grinder $230.00 4 $920.00
 02 ACME Saw $220.00 2 $440.00
 A> The unit cost of item DEF456 is not explicitly listed in the invoice; however, DEF456 refers to the ACME Grinder, which has a unit cost of $230.00.


 35% 35/100 [04:20<08:25,  7.77s/it]INFO 2024-06-26 22:36:04,370 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Can you summarize the essential invoice details such as products, quantities, and customer?
 I> INVOICE # 3017

 DATE: 21 Feb 22

 BILL TO: Acme Supplies

 156 Bunny Way

 Lagomorph, NY 11122

 | ITEM | QUANTITY | UNIT PRICE | LINE TOTAL |
 | --- | --- | --- | --- |
 | Part A | 50 | $3.05 | $152.50 |
 | Part B | 25 | $7.64 | $191.00 |
 | Part C | 50 | $2.87 | $143.50 |
 | Part D | 75 | $1.42 | $106.50 |

 TAXES: NY State Tax 8%

 SHIP VIA: FedEx Ground

 FREIGHT CHARGE: $35.50
 A> Acme Supplies has been billed for 50 Part A, 25 Part B, 50 Part C, and 75 Part D along with a freight charge of $35.50 on February 21, 2022, totaling $693.50 excluding taxes.


 36% 36/100 [04:27<08:07,  7.62s/it]INFO 2024-06-26 22:36:11,312 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What items were purchased and in which quantities?
 I> The invoice includes the following items: Laptop, Mouse, Keyboard, and Monitor.
 A> Based on the invoice, the user has purchased a Laptop (x1), a Mouse (x2), a Keyboard (x1), and a Monitor (x1).

 Q> What are the taxes and additional charges included in the invoice?
 I> 
 A> The taxes and additional charges on an invoice typically include sales tax, shipping fees, handling fees, and any miscellaneous charges or discounts. These can be found in separate line items, usually near the bottom of the invoice.


 38% 38/100 [04:36<06:49,  6.61s/it]INFO 2024-06-26 22:36:20,548 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Determine the total cost of quantity 50 for the item with code ABC123.
 I> INVOICE #10001

 DATE: 03/14/2022

 FROM: AI Corp

 123 Main St

 Seattle, WA 98101

 ITEMS:

 Code Description Quantity Per Unit Amount
 ABC123 Artificial Intelligence Module 25 $1000.00
 XYZ987 Quantum Computer 50 $5000.00
 A> The total cost for 50 units of item ABC123 would be $50,000.00 (25 units x $1000.00 per unit plus 25 additional units at $1000.00 each).

 Q> Find the address for the invoice recipient.
 I> INVOICE TO:
 Jack Doe
 XYZ Company
 1234 South High Street
 Columbus, Ohio 43207
 A> The recipient's address is 1234 South High Street, Columbus, Ohio 43207.


 40% 40/100 [04:47<06:11,  6.20s/it]INFO 2024-06-26 22:36:31,230 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What are the items included in the invoice and their quantities?
 I> INVOICE
 [...]
 ITEMS:
 QTY DESCRIPTION UNIT PRICE TOTAL
 10 Projectors $350.00 $3,500.00
 20 Laser Pointer $15.00 $300.00
 A> The items included in the invoice are 10 Projectors and 20 Laser Pointers.

 Q> Which taxes are applicable for this order?
 I> INVOICE
 [...]
 TAXES APPLICABLE: 8.25%
 A> The taxes applicable for this order are 8.25%.


 42% 42/100 [04:56<05:31,  5.72s/it]INFO 2024-06-26 22:36:40,615 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 INFO 2024-06-26 22:36:49,729 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Which customer has the highest balance?
 I> 
 A> XYZ Corp. has the highest balance of $74,492.94 among all customers.


 43% 43/100 [05:10<06:53,  7.25s/it]INFO 2024-06-26 22:36:54,605 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Kindly list all the items with their respective quantities and unit prices on the invoice.
 I> INVOICE # 4608

 DATE: 15 Mar 22

 BILL TO: Widgets Inc.

 1010 Widget Way

 Widgetville, OH 44444

 | ITEM | QUANTITY | UNIT PRICE | LINE TOTAL |
 | --- | --- | --- | --- |
 | Widget A | 20 | $29.99 | $599.80 |
 | Widget B | 30 | $19.49 | $584.70 |
 | Widget C | 50 | $14.95 | $747.50 |
 | Widget D | 75 | $8.75 | $656.25 |

 TAXES: OH State Tax 6.5%

 SHIP VIA: UPS

 FREIGHT CHARGE: $22.75
 A> - Widget A: 20 units, $29.99 each
 - Widget B: 30 units, $19.49 each
 - Widget C: 50 units, $14.95 each
 - Widget D: 75 units, $8.75 each

 With freight charge: $22.75

 Q> State the tax rate applied to the invoice.
 I> 
 A> The tax rate applied to the invoice is 6,214.40.


 45% 45/100 [05:21<06:07,  6.68s/it]INFO 2024-06-26 22:37:05,819 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the payment term for the invoice?
 I> INVOICE # 112

 ORIG DATE 10/15/19

 DUE DATE: 11/15/19
 ```markdown
 BILL TO:
 Suzy Customer
 123 Customer Ave.
 Oceanic, NY  11111

 PURCHASE ORDER #: 1234
 ACCOUNT #: 222222
 ITEM                    QTY   PRICE   AMOUNT
 -------------------   ---  ------   -----
 Item A                   1  $300.00  $300.00
 Item B                 300  $0.25   $75.00
 Item C                    2  $15.00   $30.00
 Item D                 100  $1.00   $100.00
 -------------------   ---  ------   -----
 SUBTOTAL               403  $405.00
 TAX                     37.05
 -------------------   ---  ------
 TOTAL                   442.05
 ```
 A> The payment term for the invoice is DUE DATE: 11/15/19.

 Q> Who is the recipient of the goods in this invoice?
 I> INVOICE

 Bill To: Acme Corporation
 Address 1: 1234 Fake St.
 Address 2: Suite 300
 City, State Zip: Anytown, CA 12345

 Items:

 1. Widget A
 Quantity: 3
 Price Per Unit: $20

 2. Thing B
 Quantity: 2
 Price Per Unit: $120

 Ship To:

 Name: John Doe
 Address 1: 494 Elm Street
 Address 2:
 City, State Zip: East Meadow, NY 11554
 A> The recipient of the goods in this invoice is John Doe, located at 494 Elm Street, East Meadow, NY 11554.


 47% 47/100 [05:34<05:49,  6.59s/it]INFO 2024-06-26 22:37:18,635 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> From the email, what is the total cost for the shipment?
 I> INVOICE

 Shipment Details
 Shipping Method: Ground
 Delivery Date: 05/15/2023
 Cost: $100
 A> The total cost for the shipment in this invoice is $100.

 Q> Could you identify the phone number of the vendor from the email?
 I> INVOICE

 Vendor Details:
 Company Name: Blue Corp
 Address: 901 Industrial Ave, Cityname, State, 12345
 Phone: 123-456-7890
 Fax: 111-222-3333
 A> The phone number of the vendor is 123-456-7890.


 49% 49/100 [05:44<05:07,  6.03s/it]INFO 2024-06-26 22:37:28,302 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What are the shipping and handling charges for this invoice?
 I> INVOICE #40007

 DATE: 06/18/2023

 ITEM QUANTITY PRICE ITEM TOTAL
 Widgets 5 $100.00 $500.00
 Gadgets 10 $20.00 $200.00
 Sprockets 15 $50.00 $750.00

 TOTAL BEFORE SHIPPING AND HANDLING: $1450.00
 ESTIMATED SHIPPING: 2 Day
 ESTIMATED SHIPPING COST: $50.00
 ESTIMATED HANDLING: $25.00
 A> The shipping and handling charges for this invoice are $75.00 (Estimated Shipping: $50.00 + Estimated Handling: $25.00).

 Q> Who is the invoice sent to for INVOICE # 10101?
 I> INVOICE # 10101

 DATE: 12/25/2023

 **TO:** JSM Gadgets

 PO#: 98765432

 **FROM:** SP Tools

 ITEMS:

 Item Description Quantity Unit Cost Total Cost
 1 Check Valves 200 $5.75 $1150.00
 2 Pressure Sensors 50 $28.00 $1400.00
 3 Screws 500 $0.10 $50.00

 SUBTOTAL: $2600.00
 TAX: 8.25%
 TOTAL: $2807.00
 A> This invoice is sent to JSM Gadgets.


 51% 51/100 [05:56<04:55,  6.03s/it]INFO 2024-06-26 22:37:40,404 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Given an invoice number, find the corresponding invoice.
 I> ```python
 INVOICE NUMBERS:
 15, 21, 25, 30
 ```
 ** Invoice 21:
 ```vbnet
 INVOICE # 21

 DATE: 2/21/2024

 SHIP TO:

 Jane Doe
 J&J corp
 777 77 7th st
 Newark, NJ 56789
 Phone: 111-222-3333

 PAY TO:

 Jane Doe
 J&J corp
 222 22 2nd Ave
 Boston, MA 01234
 Phone: 123-123-1234

 TERMS: Net 30

 ITEMS:

 # | Quantity | Description | Unit Cost | Total
 ----------------------------------------------------
 1 | 27 | Odyssey Ark 55-inch Monitors | $1,952.00 | $52,704.00
 2 | 27 | Standard Keyboards | $32.00 | $864.00
 3 | 27 | Standard Mice | $11.00 | $297.00
 4 | 1 TB | Cloud Service | $99.99 | $99.99
 TOTAL: | $53,964.99
 TAX: | $3,237.90
 SHIPPING: | $0.00
 TOTAL DUE: | $57,202.89

 Signed: ___________
 ```
 A> Here's the invoice 21:
 INVOICE # 21
 ...
 (The rest of invoice 21 is the same as provided in the input field)

 Q> From an invoice, state the recipient's shipping address.
 I> 
 A> The shipping address is:
 Jane Doe
 J&J corp
 777 77 7th st
 Newark, NJ 56789


 53% 53/100 [06:09<04:49,  6.17s/it]INFO 2024-06-26 22:37:53,334 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Who sent the invoice via email?
 I> <email from John Smith on March 31, 2023>
 Subject: Invoice #1234
 Hello,
 Attached is the invoice #1234 for your review and payment as discussed.
 Best,
 John Smith
 <email attachment: Invoice#1234.pdf>
 A> The invoice was emailed by John Smith, as per the email dated March 31, 2023.

 Q> What is the due date of the invoice mentioned in the email?
 I> <email from Jane Doe on March 26, 2023>
 Subject: Invoice #5678
 Hello,
 Please find the invoice #5678 attached. Kindly process the payment by April 24, 2023.
 Best,
 Jane Doe
 <email attachment: Invoice#5678.pdf>
 A> The due date for the invoice #5678 is April 24, 2023.


 55% 55/100 [06:19<04:22,  5.82s/it]INFO 2024-06-26 22:38:03,420 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 INFO 2024-06-26 22:38:11,328 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the total cost for the invoice in the provided email?
 I> <email from John Smith on January 1, 2023>
 Subject: Invoice #12345
 Dear [Client],
 Below is the summary of the charges:
 - Consulting Fee: $2,500
 - Hardware Cost: $1,200
 - Shipping: $150
 Total: $3,850
 Thank you,
 John Smith
 A> The total cost for invoice #12345 is $3,850.

 Q> Based on the email, to whom is the invoice sent from John Smith?
 I> <email from John Smith on January 1, 2023>
 Subject: Invoice #12345
 Dear [Client],
 Below is the summary of the charges:
 - Consulting Fee: $2,500
 - Hardware Cost: $1,200
 - Shipping: $150
 Total: $3,850
 Best regards,
 John Smith
 <email attachment: invoice_12345.pdf>
 A> Based on the email, the invoice #12345 was sent from John Smith.


 57% 57/100 [06:37<04:54,  6.85s/it]INFO 2024-06-26 22:38:21,832 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the total amount of the invoice?
 I> INVOICE
 [...]
 TAX: $350
 TOTAL: $3,850.00
 A> The total amount of the invoice is $3,850.00.

 Q> Which state is the invoice from, based on the company's name?
 I> INVOICE FROM:
 Acme Inc.
 155 Main St
 San Francisco, CA 94115
 A> The invoice is from the state of California, based on the company's address.


 59% 59/100 [06:47<04:13,  6.18s/it]INFO 2024-06-26 22:38:31,123 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the quantity of item 01 in the invoice?
 I> INVOICE # 007

 DATE 2/27/2021

 ITINERARY

 Territory: Alaska

 Territory Manager: Michael Parker

 SALES EXECUTIVE

 Account Name: Maxwell Johnson

 Account Name: Emily Garcia

 INVOICE

 Bill To:

 Maxwell Johnson

 C/O NE Corp.

 12000 Prospect Ave NE

 Seattle, WA 98115

 Items:

 Code Item Name Unit Cost Quantity Total Cost
 01 Tundra Flood Covers $280.00 12 $3,360.00
 02 Yukon Jacket $150.00 25 $3,750.00
 03 Glacier Blanket $220.00 18 $3,960.00
 A> The quantity of item 01 is 12.

 Q> What is the customer's complete address in the invoice?
 I> INVOICE # 004

 DATE 12/13/2020

 ITINERARY

 Territory: Florida

 Territory Manager: Rachel Williams

 SALES EXECUTIVE

 Account Name: Mira Parker

 Account Name: Remi Martins

 INVOICE

 Bill To:

 Mira Parker

 C/O Ravensworth Pvt. Ltd.

 500 S Orange Ave

 Orlando, FL 32801

 Items:

 Code Item Name Unit Cost Quantity Total Cost
 01 Magic Lantern $780.00 2 $1,560.00
 02 Everglades Hoodie $150.00 30 $4,500.00
 03 Swamp Ice Cap $230.00 45 $10,350.00
 A> The customer's complete address is: Mira Parker, C/O Ravensworth Pvt. Ltd., 500 S Orange Ave, Orlando, FL 32801.


 61% 61/100 [07:00<04:05,  6.29s/it]INFO 2024-06-26 22:38:44,167 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the total due after taxes and shipping for the provided invoice?
 I> INVOICE # 408

 DATE: February 27, 2022

 BILL TO: Global Enterprises

 720 Eighth Avenue

 New York, NY 10036

 | ITEM | QUANTITY | UNIT PRICE | LINE TOTAL |
 | --- | --- | --- | --- |
 | M20 Monitors | 10 | $425.00 | $4,250.00 |
 | M20 Keyboard | 20 | $55.00 | $1,100.00 |
 | M20 Mouse | 10 | $35.00 | $350.00 |

 TAXES: NY State Tax 8%

 SHIPPING: Priority Mail | $45.00
 A> The total due after taxes and shipping is $5,646.00.

 Q> Identify the recipient and their contact information for this invoice.
 I> INVOICE # 1389

 DATE: 04/22/2022

 BILL TO: Lee's Electronics

 4700 Technology Drive

 Atlanta, GA 30341
 Phone: (404) 555-1212

 | ITEM | QUANTITY | UNIT PRICE | LINE TOTAL |
 | --- | --- | --- | --- |
 | LED 4K Display | 5 | $749.99 | $3,749.95 |
 | Premium Headphones | 10 | $124.95 | $1,249.50 |
 A> The recipient of this invoice is Lee's Electronics and their contact information is 4700 Technology Drive, Atlanta, GA 30341, Phone: (404) 555-1212.


 63% 63/100 [07:12<03:51,  6.26s/it]INFO 2024-06-26 22:38:56,558 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Identify the grand total of the invoice.
 I> ```vbnet
 ## INVOICE
 [...]
    SUBTOTAL: $36,280.00
    TAX: $4,205.09
    TOTAL: $40,485.09
 ```
 A> The grand total of the invoice is $40,485.09.

 Q> Who is the invoice from?
 I> ```vbnet
 ## INVOICE
 [...]
  INVOICE FROM: Company Inc.
 ```
 A> The invoice is from Company Inc.


 65% 65/100 [07:21<03:21,  5.76s/it]INFO 2024-06-26 22:39:05,756 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Can you provide the customer details from the email's invoice?
 I> The invoice shows a customer with the name "Global Inc.", located at "1234 Main St, Anytown, USA" and the email address "[[email protected]](mailto:[email protected])".
 A> The customer details from the invoice are "Global Inc.", "1234 Main St, Anytown, USA" and "[[email protected]](mailto:[email protected])".

 Q> What is the quantity of item "XYZ Model 456" on the invoice?
 I> 
 A> The quantity of item "XYZ Model 456" on the invoice is 15.


 67% 67/100 [07:31<02:59,  5.45s/it]INFO 2024-06-26 22:39:15,190 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Specify the total amount due from the invoice.
 I> 
 A> The total amount due from the invoice is 60,179.39.

 Q> What is the purchase order number in the email?
 I> "Purchase Order Number: AD34-11, Thank you for your order of three nightstands. Invoice number: INV128-34"
 A> The purchase order number in the email is AD34-11.


 69% 69/100 [07:40<02:39,  5.14s/it]INFO 2024-06-26 22:39:24,040 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the name of the customer who purchased item 02?
 I> INVOICE # 007

 DATE 2/27/2021

 ITINERARY

 Territory: Alaska

 Territory Manager: Michael Parker

 SALES EXECUTIVE

 Account Name: Maxwell Johnson

 Account Name: Emily Garcia

 INVOICE

 Bill To:

 Maxwell Johnson

 C/O NE Corp.

 12000 Prospect Ave NE

 Seattle, WA 98115

 Items:

 Code Item Name Unit Cost Quantity Total Cost
 01 Tundra Flood Covers $280.00 12 $3,360.00
 02 Yukon Jacket $150.00 25 $3,750.00
 03 Glacier Blanket $220.00 18 $3,960.00
 A> The name of the customer who purchased item 02 is Emily Garcia.

 Q> Which method was used for shipping this invoice's delivery?
 I> INVOICE

 Shipment Details
 Shipping Method: Ground
 Delivery Date: 05/15/2023
 Cost: $100
 A> Ground was used for shipping this invoice's delivery.


 71% 71/100 [07:51<02:32,  5.24s/it]INFO 2024-06-26 22:39:35,009 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Can you extract the products and quantities in the invoice?
 I> PRODUCTS

 Product 1: Laptop
 Quantity: 1
 Price: $1,500

 Product 2: Keyboard
 Quantity: 2
 Price: $72
 A> Laptop - Quantity: 1
 Keyboard - Quantity: 2

 Q> What is the billing address associated with this invoice?
 I> BILLING ADDRESS
 Billing Name: John Doe
 Street Address: 123 Main Street
 City: Springfield
 State: IL
 Zip Code: 62701
 A> Billing Name: John Doe \
 Street Address: 123 Main Street, Springfield, IL 62701


 73% 73/100 [08:00<02:17,  5.09s/it]INFO 2024-06-26 22:39:44,450 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the tax rate applicable to this invoice?
 I> # INVOICE
 ...
 TAXES APPLICABLE 7.5% $346.86
 ...
 A> The tax rate applicable to this invoice is 7.5%.

 Q> Prepare a summary of invoice #22.
 I> # INVOICE
 ...
 INVOICE # 22
 DATE: 5/12/2023
 ...
 A> Invoice #22 summary:
 - Date: 5/12/2023


 75% 75/100 [08:09<02:03,  4.93s/it]INFO 2024-06-26 22:39:53,612 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> How many items does the invoice list?
 I> INVOICE

 INVOICE # 21

 DATE: 2/21/2024

 Items:

 1 TB Cloud service 99.99 99.99

 27 Odyssey Ark 55-inch Monitors 1,952 52,704

 27 Standard Keyboards 32 864

 27 Standard Mice 11 297

 | QUANTITY  | DESCRIPTION        | UNIT  PRICE  | TOTAL   |
 |------------|------------------------------|--------------|-----------|
 | 1         | Cloud service             | 99.99      | 99.99   |
 | 27        | Odyssey Ark 55-inch Monitors | 1,952      | 52,704  |
 | 27        | Standard Keyboards       | 32         | 864    |
 | 27        | Standard Mice            | 11         | 297    |
 |           | Totals                           |           | 53,964.99 |

 SUBTOTAL: 53,964.99
 SALES TAX: 3,237.90
 SHIPPING AND HANDLING: 0.00
 TOTAL DUE: 57,202.89
 A> The invoice lists 4 items.

 Q> What was the subtotal before taxes and shipping for the invoice?
 I> INVOICE

 ...

 SUBTOTAL: 53,964.99
 SALES TAX: 3,237.90
 SHIPPING AND HANDLING: 0.00
 TOTAL DUE: 57,202.89
 A> The subtotal before taxes and shipping was 53,964.99.


 77% 77/100 [08:23<02:08,  5.57s/it]INFO 2024-06-26 22:40:07,719 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the first item description in the invoice and its corresponding quantity?
 I> INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 ## PURCHASED BY:

 John Doe J&J corp 777 77 $^{th}$ st Newark, Nj 56789 Phone: 111-222-3333

 ## COMMENTS OR SPECIAL INSTRUCTIONS:

 Due upon receipt

 | QUANTITY  | DESCRIPTION         | UNIT PRICE      | TOTAL   |
 |------------|------------------------------|-----------------------|-----------|
 | 100      | Notebook             | 567          | 56,700   |
 | 100      | Monitor                 | 987          | 98,700   |
 | 100      | Desktop                | 750          | 75,000   |
 | 100      | Mice                     | 45.6          | 4,560   |
 | 100      | Keyboard             | 67.9          | 6,790   |
 INVOICE # 21

 DATE: 2/21/2024

 PO #: 223456

 SHIP TO:

 Jane Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, Nj 56789

 Phone: 111-222-3333
 A> The first item description in the invoice is 'Notebook' and its corresponding quantity is 100.


 78% 78/100 [08:37<02:34,  7.04s/it]INFO 2024-06-26 22:40:21,616 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What's the total cost of all items on invoice 24738 and are there any applicable taxes?
 I> 
 A> The total cost of all items on invoice 24738 is 2,549.21 dollars with 154.92 dollars in taxes.

 Q> Who is the recipient of the invoice dated 2023-01-31?
 I> 
 A> The recipient of the invoice dated 2023-01-31 is John Doe.


 80% 80/100 [08:46<02:04,  6.21s/it]INFO 2024-06-26 22:40:30,733 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the total amount due as per the invoice?
 I> ```vbnet
 ## INVOICE
 [...]
  TOTAL AMOUNT DUE: $56,789.23
 ```
 A> The total amount due as per the invoice is $56,789.23.

 Q> Which items were included in the invoice and what are their respective quantities?
 I> ```vbnet
 ## INVOICE
 [...]
 ITEM: XYZ Model 456, QUANTITY: 15
 ITEM: ABC Model 789, QUANTITY: 20
 ```
 A> The invoice includes:
 - XYZ Model 456 with a quantity of 15
 - ABC Model 789 with a quantity of 20


 82% 82/100 [08:56<01:43,  5.75s/it]INFO 2024-06-26 22:40:40,306 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 INFO 2024-06-26 22:40:42,175 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the contact information for the customer in question?
 I> | Customer Name | E-mail |
 | --- | --- |
 | Acme Inc. | [[email protected]](mailto:[email protected]) |
 |  | [[email protected]](mailto:[email protected]) |
 |  | [[email protected]](mailto:[email protected]) |
 | Contact Name | E-mail |
 | John Doe | [[email protected]](mailto:[email protected]) |
 | Jane Smith | [[email protected]](mailto:[email protected]) |
 A> Acme Inc.'s contact email is [[email protected]](mailto:[email protected]).

 Q> Which invoices are beyond their due date?
 I> | Invoice Number | Customer | Due Date | Amount | Paid (Y/N) |
 | --- | --- | --- | --- | --- |
 | 12345 | Acme Inc. | 2023-02-01 | $5,500 | N |
 | 67890 | XYZ Corp. | 2023-01-15 | $3,000 | Y |
 | 111213 | Acme Inc. | 2023-02-20 | $7,000 | N |
 | 141516 | XYZ Corp. | 2023-03-01 | $6,000 | N |
 A> Invoices 12345 and 111213 are beyond their due date.


 84% 84/100 [09:10<01:37,  6.11s/it]INFO 2024-06-26 22:40:54,088 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 INFO 2024-06-26 22:40:55,494 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the total amount owed by the customer after applying the invoice?
 I> CUSTOMER: John Doe
 INVOICE:

 Particulars | Qty | Rate
 -- | -- | --
 Hardware | 2 | $500
 Software | 1 | $1,200
 Services | 3 | $340
 A> After applying this invoice, John Doe needs to pay a total of $2,040.

 Q> Which items or services did the customer purchase according to the email containing the invoice?
 I> INVOICE:

 Items/Services:

 1. (Qty: 2) 11" MacBook Air, 256GB, Silver - $1,199.00
 2. (Qty: 1) Apple Pencil (2nd Generation) - $129.00
 3. (Qty: 3) AppleCare+ for Mac - $199.00

 Subtotal: $2,527.00
 Tax: $224.74
 Total: $2,751.74
 A> The customer purchased 2 units of an 11-inch MacBook Air with 256GB and Silver version, 1 Apple Pencil (2nd Generation), and 3 AppleCare+ for Mac.


 86% 86/100 [09:22<01:25,  6.11s/it]INFO 2024-06-26 22:41:06,317 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the purchase order number associated with this invoice?
 I> INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 PO# 456789

 PURCHASED BY:

 John Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, Nj 56789

 Phone: 111-222-3333

 ITEMS:

 1 TB Cloud service $^{99.99}$/each

 5 @ $55.31 each

 SHIP VIA:

 UPS Ground Shipping

 SHIP TO:

 Jane Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, Nj 56789

 Phone: 111-222-3333

 Tax: $46.58
 A> The purchase order number associated with this invoice is 456789.

 Q> What are the items and quantities ordered in this invoice?
 I> INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 PO# 456789

 PURCHASED BY:

 John Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, NJ 56789

 Phone: 111-222-3333

 ITEMS:

 1 TB Cloud service $^{99.99}$/each

 5 @ $55.31 each

 SHIP VIA:

 UPS Ground Shipping

 SHIP TO:

 Jane Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, NJ 56789

 Phone: 111-222-3333

 Tax: $46.58
 A> The items and quantities ordered in this invoice are 1 TB Cloud service, 5 units.


 88% 88/100 [09:35<01:14,  6.23s/it]INFO 2024-06-26 22:41:19,294 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 INFO 2024-06-26 22:41:21,235 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the shipping and handling fee shown in the invoice?
 I> Invoice #1761

 Bill To:
 Beaver & Co.

 100 Green Road

 Shelbyville, ID 83112

 Ship Via: UPS

 Items:

 | Item# | Description | Quantity | Price |
 | --- | --- | --- | --- |
 | 123 | LCD Panel | 25 | $200.00 |
 | 456 | Laser Mouse | 50 | $10.00 |
 | 789 | Paper Shredder | 30 | $65.00 |

 Terms: 2/10, n/30

 Date: 01/12/2022

 NOTE: Please include the warranty in the shipment

 Shipping and Handling: $85.00

 TAX: 0%
 A> The shipping and handling fee shown in the invoice is $85.00.

 Q> Can you identify the purchaser for this invoice?
 I> INVOICE

 555 5 $^{th}$ st

 Boston, MA 01234

 Phone: 123-456-7890

 PURCHASED BY:

 John Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, NJ 56789

 Phone: 111-222-3333

 Comments or Special Instructions:

 Due upon receipt

 | QUANTITY  | DESCRIPTION    | UNIT PRICE  | TOTAL   |
 |------------|-----------------------------|-------------|----------|
 | 2         | abc             , xyz | $200.00   | $400.00 |
 | 1          | Mno             , pqr | 2000.00   | 2000.00 |
 | 3          | stu             , vwx | 500.00    | 1500.00 |

 Ship To:

 Joan Smith

 TUV Business Solutions

 123 Any Street

 New York, NY 00111

 Invoice Number: 00458

 Date: 04/14/2021

 Shipping and Handling: $100.00

 TAX RATE: 8%
 A> The purchaser for this invoice is John Doe, J&J corp, located at 777 77 $^{th}$ st, Newark, NJ 56789.


 90% 90/100 [09:51<01:08,  6.86s/it]INFO 2024-06-26 22:41:35,892 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> What is the invoice number and total amount for the purchase?
 I> ```vbnet
 ## INVOICE
 [...]
  INVOICE #: 12345
  [...]
  TOTAL: $3,850
 ```
 A> The invoice number #12345 has a total amount of $3,850.

 Q> What is the description of each charge on the invoice?
 I> <email from John Smith on January 5, 2023>
 Subject: Invoice #12345
 Dear [Client],
 Below is the summary of the charges:
 - Consulting Fee: $2,500
 - Hardware Cost: $1,200
 - Shipping: $150
 Total: $3,850
 Best regards,
 John Smith
 <email attachment: invoice_12345.pdf>
 A> The description of each charge on the invoice is: consulting fee for $2,500, hardware cost for $1,200, and shipping for $150.


 92% 92/100 [10:02<00:50,  6.33s/it]INFO 2024-06-26 22:41:46,089 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Who did the purchasing for this invoice?
 I> INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 PO# 456789

 PURCHASED BY:

 John Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, NJ 56789

 Phone: 111-222-3333

 ITEMS:

 1 TB Cloud service \$99.99/each

 5 @ \$55.31 each

 SHIP VIA:

 UPS Ground Shipping

 SHIP TO:

 Jane Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, NJ 56789

 Phone: 111-222-3333

 Tax: \$46.58
 A> The purchasing for this invoice was done by John Doe from J&J corp.

 Q> What is the total cost of the items on this invoice?
 I> INVOICE

 555 5 $^{th}$ st Boston, Ma 01234 Phone: 123-456-7890

 PO# 456789

 PURCHASED BY:

 John Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, NJ 56789

 Phone: 111-222-3333

 ITEMS:

 1 TB Cloud service $99.99/each

 5 @ $55.31 each

 SHIP VIA:

 UPS Ground Shipping

 SHIP TO:

 Jane Doe

 J&J corp

 777 77 $^{th}$ st

 Newark, NJ 56789

 Phone: 111-222-3333

 Tax: \$46.58
 A> The total cost of the items on this invoice is $288.20.


 94% 94/100 [10:15<00:38,  6.39s/it]INFO 2024-06-26 22:41:59,171 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Can you provide the total cost of items charged in the invoice?
 I> INVOICE # 011220

 INVOICE DATE: 20 DEC 2022

 ITEMS:

 Code Item Name Quantity Rate
 4398 Hose Reel 1 $112.45
 4422 Spanner Wrench 3 $37.99
 4810 Breaker Bar 1 $112.45
 9347 Power Drill 2 $101.99
 A> The total cost of items charged in the invoice is $495.87 ($112.45 + $37.99 + $112.45 + $133.03).

 Q> Which payment method should be used according to the invoice?
 I> <email from Jane Smith on April 2, 2023>
 Subject: Invoice #2819
 Hello,
 Please find attached the invoice #2819 for your review and payment. Payments can be made via ACH, wire transfer, or credit card,
 as outlined on the invoice. If you have any questions, feel free to reach out. Thanks.
 Jane Smith
 <email attachment: Invoice#2819.pdf>
 A> According to the email from Jane Smith, payment methods specified in invoice #2819 are ACH, wire transfer, and credit card.


 96% 96/100 [10:26<00:24,  6.13s/it]INFO 2024-06-26 22:42:10,257 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Find the products ordered by a customer.
 I> | Order ID | Product Name | Quantity |
 | --- | --- | --- |
 | 1001 | Notebook | 3 |
 | 1001 | Pen | 8 |
 | 1002 | Best Seller Set | 5 |
 | 1002 | Mouse | 1 |
 | 1003 | Notebook | 10 |
 | Customer | Order ID |
 | Acme Inc. | 1001 |
 | Acme Inc. | 1002 |
 A> Acme Inc. ordered Notebook, Pen, Best Seller Set, and Mouse for a total of 17 items.

 Q> What amount did the customer pay for their order?
 I> | Order ID | Product Name | Customer | Price |
 | --- | --- | --- | --- |
 | 1001 | Notebook | Acme Inc. | 4.99 |
 | 1001 | Pen | Acme Inc. | 1.29 |
 | 1002 | Best Seller Set | Acme Inc. | 21.99 |
 | 1002 | Mouse | Acme Inc. | 3.99 |
 A> Acme Inc.'s order 1001 total came to $6.28, while order 1002 totaled $25.98.


 98% 98/100 [10:37<00:11,  5.94s/it]INFO 2024-06-26 22:42:21,230 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->invoice->plain_text
 Q> Which vendor is associated with the given invoice number?
 I> ```vbnet
 ## INVOICE
 [...]
  Vendor: Camel Milk Co.
  Invoice: #9876
 ```
 A> The vendor associated with invoice number #9876 is Camel Milk Co.

 Q> How much is the total amount due, stated in the given invoice?
 I> ```vbnet
 ## INVOICE
 [...]
  TOTAL: $3,520.00
 ```
 A> The total amount due stated in the invoice is $3,520.00.


 100% 100/100 [10:46<00:00,  5.53s/it]
 100% 100/100 [10:46<00:00,  6.46s/it]
 INFO 2024-06-26 22:42:30,382 generate_data.py:609: generate_data 100 instructions generated, 15 discarded due to format (see /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/invoice/plain_text/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T22_31_43.log), 1 discarded due to rouge score
 INFO 2024-06-26 22:42:30,382 generate_data.py:613: generate_data Generation took 646.50s
 Completed 11.9 KiB/164.6 KiB (70.7 KiB/s) with 4 file(s) remaining
 upload: ../outputtopush/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T22_31_43.log to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/invoice/plain_text/discarded_Mixtral-8x7B-Instruct-v0_2024-06-26T22_31_43.log
 Completed 11.9 KiB/164.6 KiB (70.7 KiB/s) with 3 file(s) remaining
 Completed 90.4 KiB/164.6 KiB (520.7 KiB/s) with 3 file(s) remaining
 upload: ../outputtopush/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T22_31_43.json to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/invoice/plain_text/generated_Mixtral-8x7B-Instruct-v0_2024-06-26T22_31_43.json
 Completed 90.4 KiB/164.6 KiB (520.7 KiB/s) with 2 file(s) remaining
 Completed 95.3 KiB/164.6 KiB (535.1 KiB/s) with 2 file(s) remaining
 upload: ../outputtopush/test_Mixtral-8x7B-Instruct-v0_2024-06-26T22_31_43.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/invoice/plain_text/test_Mixtral-8x7B-Instruct-v0_2024-06-26T22_31_43.jsonl
 Completed 95.3 KiB/164.6 KiB (535.1 KiB/s) with 1 file(s) remaining
 Completed 164.6 KiB/164.6 KiB (791.1 KiB/s) with 1 file(s) remaining
 upload: ../outputtopush/train_Mixtral-8x7B-Instruct-v0_2024-06-26T22_31_43.jsonl to s3://instructlab-playground-demo//synthetic_data/667c664f6a6e5a6cc87eb172/compositional_skills/extraction/invoice/plain_text/train_Mixtral-8x7B-Instruct-v0_2024-06-26T22_31_43.jsonl
 compositional_skills/extraction/abstractive/key_points/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/extraction/abstractive/key_points/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/abstractive/key_points --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T22:42:32Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/extraction/abstractive/key_points/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.
 Error: An example in the taxonomy path compositional_skills->extraction->abstractive->key_points is too long for the server context size of 4096. Ensure the total number of characters across the combined question, answer, and context is less than 4896 for each example or use a server with a larger context size.
 compositional_skills/extraction/technical_paper/abstract/plain_text/qna.yaml
 ilab generate --model-family mixtral --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1 --taxonomy-path /instructlab/taxonomytar/taxonomy/compositional_skills/extraction/technical_paper/abstract/plain_text/qna.yaml --output-dir /instructlab/ibmgenerate/taxonomytar/taxonomy/compositional_skills/extraction/technical_paper/abstract/plain_text --num-instructions 100 --endpoint-url http://0.0.0.0:8080/v1 --model /instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1
 time="2024-06-26T22:42:41Z" level=warning msg="The input device is not a TTY. The --tty and --interactive flags might not work properly"
 You are using an aliased command, this will be deprecated in a future release. Please consider using `ilab data generate` instead
 Generating synthetic data using '/instructlab/models/mistralai/Mixtral-8x7B-Instruct-v0.1' model, taxonomy:'/instructlab/taxonomytar/taxonomy/compositional_skills/extraction/technical_paper/abstract/plain_text/qna.yaml' against http://0.0.0.0:8080/v1 server
 Cannot find prompt.txt. Using default prompt depending on model-family.

  0% 0/100 [00:00<?, ?it/s]Synthesizing new instructions. If you aren't satisfied with the generated instructions, interrupt training (Ctrl-C) and try adjusting your YAML files. Adding more examples may help.
 INFO 2024-06-26 22:42:50,159 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What is the main contribution of the authors?
 I> ## Deep Feature Reweighting for Medical Image Segmentation

 Dong Liu, Anqi Zhou, Wenjia Wang, Jianfei Liu, Xiaogang Wang

 ** Abstract
 Deep learning has achieved great progress in the field of medical image segmentation. However, these deep learning based methods are data-expensive and hard to generalize to different image modalities, especially when the data is scarce or class imbalanced. To improve the robustness and generalization of medical image segmentation algorithms, this paper proposes a Deep Feature Reweighting (DFR) method. The DFR method reweights the features of input medical images by using class probabilities from a pre-trained classification network. Specifically, we up-weight the feature maps corresponding to the target class at each convolutional layer. We evaluate the performance of the proposed method on three public medical image segmentation datasets and demonstrate that the DFR method can effectively improve the segmentation performance of several state-of-the-art segmentation networks, and outperform other methods for coping with scarce data and imbalanced class distribution, especially in the case of limited data.
 A> The main contribution of the authors is a Deep Feature Reweighting (DFR) method for medical image segmentation. The DFR method reweights the features of input medical images by using class probabilities from a pre-trained classification network, which improves the robustness and generalization of deep learning based medical image segmentation algorithms.


  1% 1/100 [00:07<11:34,  7.01s/it]INFO 2024-06-26 22:42:57,174 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What is the main issue that the technique addresses?
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> The main issue that the technique addresses is that existing private synthetic data generation algorithms are agnostic to downstream tasks, and end users may have specific requirements that the synthetic data must satisfy. The technique addresses the problem by introducing a post-processing approach that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality.


  2% 2/100 [00:13<11:03,  6.77s/it]INFO 2024-06-26 22:43:03,771 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> Identify the primary techniques used for generating private synthetic data in the paper.
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> The primary techniques used for generating private synthetic data in the paper are GAN-based, marginal-based, and workload-based methods.

 Q> What are the efficiency improvements made by the technique described in the paper, compared to previous approaches for generating private synthetic data?
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> The technique described in the paper improves efficiency by using an efficient stochastic first-order algorithm to find optimal resampling weights, instead of generating new data to satisfy the specific requirements. This approach is shown to consistently improve the utility of synthetic data across benchmark datasets and state-of-the-art synthetic data generation algorithms.


  4% 4/100 [00:26<10:25,  6.51s/it]INFO 2024-06-26 22:43:16,494 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> Can you describe the main steps of the proposed technique for post-processing private synthetic data for improving utility on selected measures?
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights.
 A> The main steps of the proposed technique are: (1) resampling from the synthetic data to filter out samples that do not meet the selected utility measures, and (2) using an efficient stochastic first-order algorithm to find optimal resampling weights. This approach improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality.

 Q> What datasets were used to evaluate the proposed technique for post-processing private synthetic data for improving utility on selected measures?
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> The proposed technique for post-processing private synthetic data for improving utility on selected measures was evaluated using multiple benchmark datasets, including a variety of synthetic data generation algorithms. The results consistently showed improvement in utility, while preserving strong privacy guarantees and dataset quality.


  6% 6/100 [00:39<10:13,  6.52s/it]INFO 2024-06-26 22:43:29,567 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What are the key features of the proposed technique?
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab

 ## Abstract

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights.
 A> The key features of the proposed technique are the post-processing of existing private synthetic data generation algorithms and the improvement of the utility of the synthetic data with respect to measures selected by the end user, while preserving privacy guarantees and dataset quality. The technique involves resampling from the synthetic data and using an efficient stochastic first-order algorithm to find optimal resampling weights.

 Q> What is the primary concern that the technique seeks to address?
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> The primary concern that the technique seeks to address is the fact that existing private synthetic data generation algorithms are agnostic to downstream tasks, and end users may have specific requirements that the synthetic data must satisfy. The technique addresses the problem by introducing a post-processing approach that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality.


  8% 8/100 [00:52<10:08,  6.61s/it]INFO 2024-06-26 22:43:43,045 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What specific measures does the technique improve for the utility of synthetic data?
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab

 ## Abstract

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> The specific measures the technique improves for the utility of synthetic data are the ones selected by the end user, which are related to downstream tasks.

 Q> How does the post-processing technique preserve strong privacy guarantees for the synthetic data?
 I> 
 A> The post-processing technique preserves strong privacy guarantees for the synthetic data by using an efficient stochastic first-order algorithm to find optimal resampling weights while filtering out samples that do not meet the utility measures. This is performed within the same privacy guarantees as the initial generation of synthetic data.


 10% 10/100 [01:04<09:25,  6.28s/it]INFO 2024-06-26 22:43:54,474 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 INFO 2024-06-26 22:43:59,659 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What are the main steps involved in the proposed post-processing technique for improving the utility of private synthetic data on selected measures?
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights.
 A> The main steps involved in the proposed post-processing technique for improving the utility of private synthetic data on selected measures are resampling from the synthetic data to filter out samples that do not meet the selected utility measures, and using an efficient stochastic first-order algorithm to find optimal resampling weights.

 Q> How does the proposed post-processing technique for improving the utility of private synthetic data on selected measures preserve privacy guarantees and dataset quality?
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights.
 A> The proposed post-processing technique for improving the utility of private synthetic data on selected measures preserves privacy guarantees and dataset quality by resampling from the synthetic data to filter out samples that do not meet the selected utility measures, and using an efficient stochastic first-order algorithm to find optimal resampling weights that minimize the impact on privacy guarantees and dataset quality.


 12% 12/100 [01:22<10:34,  7.21s/it]INFO 2024-06-26 22:44:12,433 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What are the limitations of the current state-of-the-art synthetic data generation algorithms discussed in the paper?
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> The limitations of the current state-of-the-art synthetic data generation algorithms discussed in the paper include not taking into account the downstream use cases of the synthetic data in the data generation process and not meeting specific requirements end users may have for synthetic datasets, resulting in reduced utility for their downstream use cases.

 Q> What is the main contribution of this paper?
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> The main contribution of this paper is a post-processing technique that improves the utility of private synthetic data for selected measures while preserving privacy guarantees and dataset quality.


 14% 14/100 [01:35<10:00,  6.98s/it]INFO 2024-06-26 22:44:25,471 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> On what specific email are you performing the extraction of content from?
 I> 
 A> We are performing the extraction of content from the email titled "Meeting Agenda for Next Week" sent by John Lee on [date] at [time].

 Q> Identify the main topic of the email from which you are extracting content.
 I> ## Meeting Agenda for Next Week

 Dear Team,

 I hope you are all doing well. I would like to share the agenda for our meeting next week. We will be discussing the following topics:

 1. Project Updates
 - [Project Name]
 - [Project Name]

 2. Budget Plan
 - Summary of current financial status
 - Planned expenditures

 3. Staffing Updates
 - New hires
 - Training initiatives

 4. Q&A

 Thank you and I look forward to seeing everyone next week!

 Best regards,
 John Lee
 A> The main topic of the email from which we are extracting content is the agenda for the upcoming team meeting, which covers project updates, budget plan, staffing updates, and Q&A.


 16% 16/100 [01:45<08:54,  6.36s/it]INFO 2024-06-26 22:44:35,573 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What are the limitations of the exisiting methods for generating private synthetic data mentioned in the paper?
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> Existing methods for generating private synthetic data are task-agnostic and may not always meet specific requirements of end users, leading to reduced utility for their downstream use cases.

 Q> Summarize the proposed solution for improving the utility of private synthetic data.
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> A post-processing technique that improves the utility of private synthetic data by resampling from the synthetic data and filtering out samples that do not meet specific utility measures, while preserving strong privacy guarantees and dataset quality.


 18% 18/100 [01:58<08:42,  6.37s/it]INFO 2024-06-26 22:44:48,358 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> How does the proposed technique for post-processing private synthetic data for improving utility on selected measures preserve strong privacy guarantees?
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> The proposed technique for post-processing private synthetic data preserves strong privacy guarantees by resampling from the synthetic data to filter out samples that do not meet the selected utility measures, while using an efficient stochastic first-order algorithm to find optimal resampling weights. This process ensures that the privacy of the original data is not compromised, while increasing the utility of the synthetic data.

 Q> Given a specific dataset, how could the proposed post-processing technique be used to improve the utility of private synthetic data on selected measures?
 I> The specific dataset is the Adult Income dataset, with the following features: age, workclass, education, education-num, marital-status, occupation, relationship, race, sex, capital-gain, capital-loss, hours-per-week, native-country, and income.

 ** Abstract
 <noinput>
 A> To improve the utility of private synthetic data for the Adult Income dataset, the proposed post-processing technique could be used by first identifying specific utility measures that are important to downstream tasks. After generating synthetic data, resampling weights could be optimized using an efficient stochastic first-order algorithm to filter out samples that do not meet the selected utility measures. This process would increase the utility of the synthetic data on these measures, while preserving strong privacy guarantees and dataset quality.


 20% 20/100 [02:10<08:28,  6.36s/it]INFO 2024-06-26 22:45:00,996 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What data generation methods does the paper mention as current approaches?
 I> <noinput>
 ** Abstract
 The paper mentions GAN-based, marginal-based, and workload-based methods as current approaches to data generation.
 A> The paper discusses three current data generation methods: GAN-based, marginal-based, and workload-based methods.

 Q> What is one significant limitation of current data generation methods?
 I> <noinput>
 ** Abstract
 <noinput>
 A> Current data generation methods lack taking into account the downstream use cases of the synthetic data in the data generation process, which can lead to synthetic data not meeting specific user requirements and reducing downstream utility.


 22% 22/100 [02:20<07:35,  5.84s/it]INFO 2024-06-26 22:45:10,314 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> Give an example of a selected measure for improving the utility of synthetic data in the paper.
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> An example of a selected measure for improving the utility of synthetic data in the paper is the skewness of the salary distribution in a synthetic dataset that simulates employee salary data for a company.

 Q> What is the objective of the resampling process in the post-processing technique described in the paper?
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> The objective of the resampling process in the post-processing technique described in the paper is to improve the utility of the synthetic data with respect to selected measures, while preserving strong privacy guarantees and dataset quality.


 24% 24/100 [02:33<07:38,  6.03s/it]INFO 2024-06-26 22:45:23,282 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What kind of private synthetic data generation algorithms is this paper concerned with?
 I> <noinput>

 ** Abstract
 <noinput>
 A> This paper is concerned with private synthetic data generation algorithms that are agnostic to downstream tasks, meaning they do not specifically account for end user requirements.

 Q> How does the proposed post-processing technique preserve privacy guarantees in the synthetic data?
 I> <noinput>

 ** Abstract
 <noinput>
 A> The proposed post-processing technique preserves privacy guarantees in the synthetic data by resampling from the existing synthetic data to filter out samples that do not meet selected measures, rather than altering or adding data to the synthetic dataset directly.


 26% 26/100 [02:42<06:56,  5.63s/it]INFO 2024-06-26 22:45:32,717 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> Could you briefly describe the problem the paper is addressing?
 I> 
 A> The paper addresses the problem that existing private synthetic data generation algorithms are agnostic to downstream tasks and do not take into account the specific requirements of the end user. This could significantly reduce the utility of the data for downstream use. The paper aims to improve the utility of the synthetic data while preserving strong privacy guarantees and dataset quality.

 Q> What are the steps involved in the proposed solution?
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab

 ## Abstract

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights.
 A> The steps involved in the proposed solution are resampling from the synthetic data and filtering out samples that do not meet the selected utility measures, and using an efficient stochastic first-order algorithm to find optimal resampling weights.


 28% 28/100 [02:53<06:45,  5.63s/it]INFO 2024-06-26 22:45:43,932 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What use cases does the proposed solution address?
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab

 ## Abstract

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> The proposed solution addresses use cases where end users have specific requirements for synthetic datasets to be successfully analyzed by their existing data science pipelines, which may not always be met by synthetic data generated by existing methods.

 Q> What is the primary goal of the proposed technique?
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab

 ## Abstract

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> The primary goal of the proposed technique is to improve the utility of private synthetic data for specific downstream tasks, while preserving strong privacy guarantees and dataset quality.


 30% 30/100 [03:07<06:55,  5.94s/it]INFO 2024-06-26 22:45:57,244 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What are the input data characteristics, domains, and sample sizes used in their experiments?
 I> <noinput>
 ** Abstract
 In the provided abstract, the authors discuss their experiments applying a post-processing technique to improve the utility of private synthetic data for benchmark datasets. However, no specific details regarding the input data characteristics, domains, and sample sizes used in these experiments are outlined in the text.
 A> The authors conducted experiments using multiple benchmark datasets with specified characteristics, domains, and sample sizes. However, these details are not provided in the abstract.

 Q> How does this method address the challenge of trade-offs between utility and privacy guarantees?
 I> <noinput>
 ** Abstract
 <noinput>
 A> In the provided abstract, the authors mention that their post-processing method can improve utility while preserving strong privacy guarantees for the synthetic data. However, the specific methodology or strategy for addressing trade-offs between utility and privacy guarantees is not discussed or outlined in the abstract.


 32% 32/100 [03:16<06:23,  5.64s/it]INFO 2024-06-26 22:46:07,127 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> Identify the techniques used in this paper to preserve strong privacy guarantees and dataset quality while improving synthetic data utility for downstream use.
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab

 ## Abstract

 [...] Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights.

 ## 1 Introduction

 [...] Differential privacy (DP) is utilized effectively in various settings for privacy protection.
 A> The paper uses resampling from the synthetic data to filter out samples that do not meet specific utility measures and applies an efficient stochastic first-order algorithm to find optimal resampling weights. In addition, the technique is grounded in differential privacy (DP) to preserve strong privacy guarantees and dataset quality while improving synthetic data utility for downstream use.

 Q> To demonstrate the effectiveness of the proposed post-processing technique, what evaluation method is used to compare the results on multiple benchmark datasets and state-of-the-art synthetic data generation algorithms?
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab

 ## Abstract

 [...] Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.

 ## 1 Introduction

 [...] There is significant work introducing new DP synthetic data generation mechanisms, including GAN-based, marginal-based, and workload-based methods.
 A> The proposed post-processing technique is evaluated using comprehensive numerical experiments, intending to demonstrate its performance and ability to improve the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.


 34% 34/100 [03:29<06:23,  5.82s/it]INFO 2024-06-26 22:46:19,590 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> Find and summarize the main contribution of the paper.
 I> <noinput>

 ** Abstract
 ## A Novel Approach for Compressive Sensing with Structured Sparsity

 Compressive sensing (CS) is an effective technique for acquiring signals in a compressed fashion. However, existing CS algorithms often assume unstructured sparsity or group sparsity, which limits the representation power of sparse signals and the efficiency of CS algorithms. In this paper, we propose a novel approach for compressive sensing with structured sparsity, which uses a structured sparsity regularizer and the alternating direction method of multipliers (ADMM) algorithm to efficiently recover signals with complex structures. We demonstrate that our approach outperforms existing unstructured sparsity and group sparsity algorithms in terms of both signal reconstruction quality and computational efficiency, using both synthetic and real-world datasets. Our work provides a new perspective on compressive sensing for signals with various complex structures.
 A> The main contribution of the paper is proposing a novel approach for compressive sensing with structured sparsity, which uses a structured sparsity regularizer and the ADMM algorithm to efficiently recover signals with complex structures. The authors show that their approach outperforms existing unstructured sparsity and group sparsity algorithms, demonstrating its potential for various complex structures.

 Q> In the email, identify the staffing updates section and list the subtopics.
 I> ## Meeting Agenda for Next Week

 Dear Team,

 I hope you are all doing well. I would like to share the agenda for our meeting next week. We will be discussing the following topics:

 1. Project Updates
 - [Project Name]
 - [Project Name]

 2. Budget Plan
 - Summary of current financial status
 - Planned expenditures

 3. Staffing Updates
 - New hires
 - Training initiatives

 4. Q&A

 Thank you and I look forward to seeing everyone next week!

 Best regards,
 John Lee
 A> The staffing updates section in the email includes the following subtopics: new hires and training initiatives.


 36% 36/100 [03:41<06:20,  5.94s/it]INFO 2024-06-26 22:46:32,204 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 INFO 2024-06-26 22:46:34,580 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> Can you name one of the synthetic data generation algorithms that were evaluated?
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> One of the synthetic data generation algorithms that were evaluated is the GAN-based synthetic data generation algorithm.

 Q> How was the proposed technique for post-processing private synthetic data for improving utility on selected measures validated?
 I> <noinput>

 ** Abstract
 ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights. Through comprehensive numerical experiments, we demonstrate that our approach consistently improves the utility of synthetic data across multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.
 A> The proposed technique for post-processing private synthetic data for improving utility on selected measures was validated through comprehensive numerical experiments, using multiple benchmark datasets and state-of-the-art synthetic data generation algorithms.


 38% 38/100 [03:57<06:38,  6.43s/it]INFO 2024-06-26 22:46:47,209 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What kind of data is used in this work?
 I> ## An Analysis of User Behavior and Feedback on a Reading Website

 John Smith, Jane Doe

 ** Abstract
 This paper analyzes user behavior and feedback on a reading website. The authors collected data on users’ reading patterns, including the time spent on each page, the number of pages viewed, and the frequency of clicks. In addition, the authors collected user feedback through a survey and analyzed the comments and ratings given by users.
 A> The authors used data on users’ reading patterns and user feedback on a reading website for their analysis.

 Q> What is the performance of the approach proposed in the paper?
 I> ## Object Detection in Videos using Tubelet-based Spatial-Temporal Attention

 Hao Wang, Lei Zhang, Huchuan Lu

 ** Abstract
 Object detection in videos is an important task in computer vision. In this paper, the authors propose a Tubelet-based Spatial-Temporal Attention (TSTA) method for object detection in videos. The TSTA method captures both spatial and temporal information of objects in videos to improve detection performance. The authors evaluated the performance of the TSTA method on two public video object detection datasets and achieved superior results compared to state-of-the-art methods.
 A> The Tubelet-based Spatial-Temporal Attention (TSTA) method proposed in the paper outperformed state-of-the-art methods for object detection in videos on two public datasets.


 40% 40/100 [04:08<06:10,  6.17s/it]INFO 2024-06-26 22:46:58,327 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What is the problem that the authors aim to solve?
 I> ## Post-processing Private Synthetic Data for Improving Utility on Selected Measures

 Hao Wang, Shivchander Sudalairaj, John Henning, Kristjan Greenewald, Akash Srivastava ∗ MIT-IBM Watson AI Lab

 ## Abstract

 Existing private synthetic data generation algorithms are agnostic to downstream tasks. However, end users may have specific requirements that the synthetic data must satisfy. Failure to meet these requirements could significantly reduce the utility of the data for downstream use. We introduce a post-processing technique that improves the utility of the synthetic data with respect to measures selected by the end user, while preserving strong privacy guarantees and dataset quality. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures, using an efficient stochastic first-order algorithm to find optimal resampling weights.
 A> The problem that the authors aim to solve is the reduction in the utility of existing private synthetic data generation algorithms for downstream tasks due to their agnosticism to end user requirements.

 Q> For what type of use case is the proposed solution most suitable?
 I> 
 A> The proposed solution is most suitable for use cases where end users have specific requirements for the synthetic data used in downstream tasks and the existing private synthetic data generation algorithms do not meet these requirements.


 42% 42/100 [04:19<05:45,  5.95s/it]INFO 2024-06-26 22:47:09,205 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> Which Datasets were used to train and evaluate their model?
 I> ## Object Detection in Videos using Tubelet-based Spatial-Temporal Attention

 Hao Wang, Lei Zhang, Huchuan Lu

 ** Abstract
 Object detection in videos is an important task in computer vision. In this paper, the authors propose a Tubelet-based Spatial-Temporal Attention (TSTA) method for object detection in videos. The TSTA method captures both spatial and temporal information of objects in videos to improve detection performance. The authors evaluated the performance of the TSTA method on two public video object detection datasets, namely, ImageNet VID and UCF101.
 A> The authors evaluated the Tubelet-based Spatial-Temporal Attention (TSTA) method for object detection in videos using two public datasets, ImageNet VID and UCF101.

 Q> What was the evaluation metric used in the study?
 I> ## Evaluating Neural Architecture Search Methods for Image Classifiers

 Ying Liu, Ziyan Wu, Qiang Yang, Ming-Hsuan Yang

 ** Abstract
 Neural Architecture Search (NAS) has achieved great success in automated deep models. However, NAS methods require a significant amount of time and resources for evaluation. In this paper, the authors conduct a comprehensive evaluation of NAS methods for image classifiers. They propose a new evaluation metric, named Accuracy-Latency Pareto Frontier, that comprehensively considers both accuracy and latency. The authors evaluated several state-of-the-art NAS algorithms and demonstrated the effectiveness of the proposed metric.
 A> The authors evaluated the performance of NAS methods for image classifiers using a new evaluation metric, named Accuracy-Latency Pareto Frontier, that considers both accuracy and latency.


 44% 44/100 [04:30<05:32,  5.94s/it]INFO 2024-06-26 22:47:21,055 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What is the problem addressed by the authors?
 I> <noinput>

 ** Abstract
 Recent studies have found that human behavior in response to a cybersecurity warning is not always helpful or optimal, reducing the effectiveness of the warning. To address this problem, researchers in human-computer interaction have proposed various techniques for making cybersecurity warnings more effective. However, these techniques are mostly user-centric and do not consider the potential impact of user behavior on security-critical networked systems. This paper proposes an attack-centric cybersecurity warning design framework that considers both user behavior and the security of networked systems. We demonstrate the effectiveness of the proposed framework through a case study of a distributed denial of service (DDoS) attack warning system. Our results show that the attack-centric warning design framework can significantly improve networked system security and user behavior compared to traditional user-centric design methods.
 A> The authors address the problem of ineffective human behavior in response to cybersecurity warnings, which reduces the effectiveness of the warnings. They propose an attack-centric cybersecurity warning design framework that considers both user behavior and the security of networked systems.


 45% 45/100 [04:37<05:30,  6.01s/it]INFO 2024-06-26 22:47:27,380 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> For what type of study does this email discuss the experimental design?
 I> <noinput>
 ** Abstract
 <noinput>

 ** Email Content
 ---
 Dear Team,
 We are currently planning a study to test a new method for addressing traffic congestion in urban centers. The study will consist of several key components:
 1. Selecting 5 cities at random to perform the study
 2. Collecting data on both traffic patterns and public transportation utilization rates for a period of 3 months prior to the implementation of the new method.
 3. Implementing the new method and collecting an additional 6 months of traffic and public transportation data.
 4. Performing a statistical analysis to assess the effectiveness of the new method
 ---
 A> The email discusses the experimental design for a study that plans to test a new traffic congestion method. The study components include selecting 5 cities, collecting traffic and public transportation data for 3 months before and 6 months after implementing the new method, and performing a statistical analysis to assess the method's effectiveness.

 Q> What is the main focus of this study, as described in this abstract?
 I> <noinput>
 ** Abstract
 We demonstrate the efficacy of an RNA-binding protein called QKI in coordinating astrocyte-to-neuron conversion by reprogramming primary human astrocytes into functional neurons, which opens the door to exciting potential treatments for neurodegenerative diseases such as ALS and Alzheimer’s.
 A> The main focus of this study is the demonstration of the efficacy of an RNA-binding protein called QKI in coordinating astrocyte-to-neuron conversion by reprogramming primary human astrocytes into functional neurons, potentially providing a path for treatments for neurodegenerative diseases such as ALS and Alzheimer’s.


 47% 47/100 [04:48<05:15,  5.96s/it]INFO 2024-06-26 22:47:39,079 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> Which features does the model consider to generate recommendations?
 I> ## User-Centric Recommendation with Neural Attentions

 Hao Wang, Xu Chen, Hao Zhang, Qiang Yang ∗ Department of Computer Science and Engineering, The Hong Kong University of Science and Technology

 ## Abstract

 Recommender systems need to consider different features to meet diverse user requirements and improve user satisfaction. In existing methods, neural attention techniques usually attend to different parts of users' historical behavior records uniformly, regardless of the contents in these records, leading to potentially irrelevant features being included in making recommendations. In this paper, we propose to capture the varying importance of different features of users' historical behavior records with content-dependent attentions for recommendation. We propose two variants of neural attentions and evaluate them on two public datasets and one real-world industry dataset. Experimental results show that our proposed methods outperform existing methods and significantly improve user-centric recommendation performance.
 A> The model considers different features of users' historical behavior records, paying attention to them with content-dependent methods, and evaluating the importance of the features to improve recommendation performance.

 Q> What techniques were applied for the analysis of the model's performance?
 I> ## Evaluating Relative Importance of Features in Clustering based on Framework of Gramian Angular Fields and Graph Neural Network

 Muhammad Usama, Turab Shah, Saad Bin Azam, Ahsen Maqsood ∗ Department of Computer Science, University of Malaya

 ## Abstract

 This paper proposes a novel technique to analyze the relative importance of features in clustering. The technique represents data points using the framework of Gramian Angular Fields (GAF) and constructs a graph embedded with the GAF representation. Then, it employs a multi-layer Graph Neural Network (GNN) to derive attributes from the graph that signify the relative importance of features in clustering. The clusters are formulated via spectral clustering having optimal affinity matrix as input. The technique's performance is evaluated on three datasets, yielding a significant drop in clustering error compared with the state-of-the-art techniques.
 A> The techniques applied for the analysis of the model's performance in this study include representing data points with the framework of Gramian Angular Fields, constructing a graph embedded with GAF, employing a multi-layer Graph Neural Network to derive attributes, and applying spectral clustering with an optimal affinity matrix as input.


 49% 49/100 [05:02<05:14,  6.18s/it]INFO 2024-06-26 22:47:52,355 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> Can you identify the proposed solution for improving the utility of synthetic data?
 I> <noinput>
 ** Abstract
 <...> We introduce a post-processing technique that improves the utility of synthetic data with respect to measures selected by the end user. Our technique involves resampling from the synthetic data to filter out samples that do not meet the selected utility measures <...>
 A> The proposed solution for improving the utility of synthetic data is a post-processing technique that resamples the synthetic data to better meet selected utility measures.

 Q> Which privacy guarantees and dataset quality are preserved by the proposed post-processing technique?
 I> <noinput>
 ** Abstract
 <...> we show that our technique preserves strong privacy guarantees and dataset quality.
 A> The proposed post-processing technique preserves strong privacy guarantees and dataset quality.


 51% 51/100 [05:11<04:40,  5.73s/it]INFO 2024-06-26 22:48:01,865 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What is the main contribution of this paper about binary classification on imbalanced datasets?
 I> ## Learning with Label Proportions for Binary Classification on Imbalanced Datasets

 Sabino Silva, Luiz Gomes, Hugo Carvalho ∗ Department of Computer Science, Universidade Federal de Minas Gerais

 ## Abstract

 Binary classification on imbalanced datasets is a challenging task. Existing techniques often involve sampling or cost-sensitive methods, but they can be inefficient or ineffective. In this paper, we propose a new method based on learning with label proportions. We introduce the multi-prototypes algorithm for binary classification on imbalanced datasets and show that it improves the classifier's performance. The method uses a set of prototypes for each class, selected from the original data, to represent the data distribution. The prototypes are then used to build a cost-matrix that allows for efficient learning. We evaluate our proposed method and compare it with state-of-the-art techniques. Our experimental results show that the multi-prototypes algorithm achieves better performance than existing methods.
 A> The main contribution of the paper is the introduction of a new method based on learning with label proportions for binary classification on imbalanced datasets, which improves the classifier's performance using a set of prototypes for each class to represent the data distribution and build a cost-matrix.

 Q> What is the main idea of the proposed framework for effective anomaly detection?
 I> ## Effective Anomaly Detection: A Framework Combining Clustering and Classification Techniques

 John Smith, Jane Doe ∗ Department of Computer Science, Stanford University

 ## Abstract

 Anomaly detection is a critical task in many fields. Current techniques often rely solely on either clustering or classification methods, which can result in suboptimal detection performance. In this paper, we propose a new framework that combines both clustering and classification techniques for effective anomaly detection. Our framework uses clustering to identify anomalous clusters and classification to identify anomalous samples within these clusters. We evaluate our proposed framework and compare it with existing techniques. Our experimental results show that our framework outperforms existing methods in detecting anomalies, making it a promising approach for effective anomaly detection.
 A> The main idea of the proposed framework for effective anomaly detection is to combine both clustering and classification techniques, using clustering to identify anomalous clusters and classification to identify anomalous samples within these clusters.


 53% 53/100 [05:24<04:40,  5.96s/it]INFO 2024-06-26 22:48:14,828 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> What email communication system was used to send and receive the internal email communications?
 I> The email communication system used to send and receive the internal email communications was Google's Gmail.
 ** Abstract
 <noinput>
 A> Google's Gmail was used as the email communication system for sending and receiving internal email communications.

 Q> Identify the methods utilized to extract pertinent content from the collection of internal emails.
 I> The methods utilized to extract pertinent content from the collection of internal emails included simple keyword matches for specific phrases of interest and natural language processing to identify relevant themes or key concepts.
 ** Abstract
 <noinput>
 A> The methods used to extract pertinent content from the collection of internal emails included the use of simple keyword matching for specific phrases of interest and natural language processing to identify relevant themes or key concepts.


 55% 55/100 [05:34<04:10,  5.57s/it]INFO 2024-06-26 22:48:24,231 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> Can you provide an example of a downstream task that the synthetic data can be used for?
 I> <noinput>
 ** Abstract
 synthetic data must satisfy specific requirements of end users for downstream tasks.
 A> An example of a downstream task for which the synthetic data might be used is predicting the likelihood of heart disease for patients, given their medical records.

 Q> Which specific requirements of end users are not met by existing private synthetic data generation algorithms?
 I> <noinput>
 ** Abstract
 However, end users may have specific requirements that the synthetic data must satisfy.
 A> Existing private synthetic data generation algorithms may not meet specific requirements of end users, such as the need for synthetic data to be useful for downstream tasks that involve predicting rare or low-probability events.


 57% 57/100 [05:43<03:47,  5.30s/it]INFO 2024-06-26 22:48:33,579 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> Explain how the model's performance is measured and evaluated in this study.
 I> 
 A> The model's performance is measured and evaluated in this study using various assessment metrics, including precision, recall, and F1 score. The authors also compare their proposed method against existing state-of-the-art techniques for binary classification on imbalanced datasets to provide a comprehensive evaluation of the model's effectiveness.

 Q> Summarize the data requirements for implementing the multi-prototypes algorithm.
 I> 
 A> To implement the multi-prototypes algorithm, researchers need a dataset containing at least two classes with varying degrees of imbalance. Each class should have a sufficient number of instances to allow for the selection of multiple prototypes that represent the data distribution effectively. Ideally, the dataset should be pre-processed to ensure consistency and relevance to the binary classification task at hand.


 59% 59/100 [05:53<03:31,  5.15s/it]INFO 2024-06-26 22:48:43,221 generate_data.py:505: generate_data Selected taxonomy path compositional_skills->extraction->technical_paper->abstract->plain_text
 Q> Which mobile device platforms does the paper support?
 I> <noinput>
 ** Abstract
 In this paper, we introduce a new user profiling framework for mobile devices that provides high-quality user profiling data with minimal overhead. Our framework supports both iOS and Android mobile devices, and it can be used for various applications such as mobile personalization, context-aware advertising, and user