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@ -329,14 +329,26 @@ def find_entities(tsv_file, tsv_out_file, ner_rest_endpoint, ned_rest_endpoint,
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tsv, ner_result = ner(tsv, ner_rest_endpoint)
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tsv, ner_result = ner(tsv, ner_rest_endpoint)
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if ned_rest_endpoint is not None:
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elif os.path.exists(tsv_file):
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print('Using NER information that is already contained in file: {}'.format(tsv_file))
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tmp = tsv.copy()
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tmp['sen'] = (tmp['No.'] == 0).cumsum()
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ner_result = [[{'word': row.TOKEN, 'prediction': row['NE-TAG']} for _, row in sen.iterrows]
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for _, sen in tmp.groupby('sen')]
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else:
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raise RuntimeError("Either NER rest endpoint or NER-TAG information within tsv_file required.")
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if ned_rest_endpoint is not None:
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tsv, ned_result = ned(tsv, ner_result, ned_rest_endpoint, json_file=ned_json_file, threshold=ned_threshold)
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tsv, ned_result = ned(tsv, ner_result, ned_rest_endpoint, json_file=ned_json_file, threshold=ned_threshold)
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if ned_json_file is not None and not os.path.exists(ned_json_file):
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if ned_json_file is not None and not os.path.exists(ned_json_file):
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with open(ned_json_file, "w") as fp_json:
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with open(ned_json_file, "w") as fp_json:
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json.dump(ned_result, fp_json, indent=2, separators=(',', ': '))
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json.dump(ned_result, fp_json, indent=2, separators=(',', ': '))
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print('Writing to {}...'.format(tsv_out_file))
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print('Writing to {}...'.format(tsv_out_file))
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tsv.to_csv(tsv_out_file, sep="\t", quoting=3, index=False)
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tsv.to_csv(tsv_out_file, sep="\t", quoting=3, index=False)
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