flair_ner_chase_init.py

from flair.data import Sentence
from flair.models import SequenceTagger

tagger = SequenceTagger.load('ner')

filename = 'ts.txt'
out_filename = 'ts_with_entities.txt'

cnt = 0
with open(filename) as f:
  with open(out_filename, 'w') as of:
    for line in f.readlines():
      line = line.replace('\n', '')
      # run model
      sentence = Sentence(line)
      tagger.predict(sentence)
      # extract entities
      entities = [f'{span.text} ({span.tag})' for span in sentence.get_spans('ner')]
      entities_string = ', '.join(entities)
      # write to file
      of.write(f'{line}\n')
      of.write(f'😁: {entities_string}\n')
      cnt = cnt + 1
      if cnt % 100 == 0:
        print(f'Processed {cnt} lines')