Created
January 22, 2018 15:52
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[NEE]Basic example of using NLTK for name entity extraction.#python #nltk
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| import nltk | |
| with open('sample.txt', 'r') as f: | |
| sample = f.read() | |
| sentences = nltk.sent_tokenize(sample) | |
| tokenized_sentences = [nltk.word_tokenize(sentence) for sentence in sentences] | |
| tagged_sentences = [nltk.pos_tag(sentence) for sentence in tokenized_sentences] | |
| chunked_sentences = nltk.ne_chunk_sents(tagged_sentences, binary=True) | |
| def extract_entity_names(t): | |
| entity_names = [] | |
| if hasattr(t, 'label') and t.label: | |
| if t.label() == 'NE': | |
| entity_names.append(' '.join([child[0] for child in t])) | |
| else: | |
| for child in t: | |
| entity_names.extend(extract_entity_names(child)) | |
| return entity_names | |
| entity_names = [] | |
| for tree in chunked_sentences: | |
| # Print results per sentence | |
| # print extract_entity_names(tree) | |
| entity_names.extend(extract_entity_names(tree)) | |
| # Print all entity names | |
| #print entity_names | |
| # Print unique entity names | |
| print set(entity_names) |
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