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Fix long text processing
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cd976692d6
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1
nlp
1
nlp
@ -71,6 +71,7 @@ class NLPPipeline(WorkflowRunner):
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'''
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'''
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nlp_tasks = []
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nlp_tasks = []
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n_cores = max(1, int(self.getNCores() / len(self.jobs)))
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n_cores = max(1, int(self.getNCores() / len(self.jobs)))
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mem_mb = min(n_cores * 2048, int(self.getMemMb() / len(self.jobs)))
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for i, job in enumerate(self.jobs):
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for i, job in enumerate(self.jobs):
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output_file = os.path.join(job.output_dir, '{}.nopaque-stand-off.json'.format(job.name)) # noqa
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output_file = os.path.join(job.output_dir, '{}.nopaque-stand-off.json'.format(job.name)) # noqa
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cmd = 'spacy-nlp'
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cmd = 'spacy-nlp'
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12
spacy-nlp
12
spacy-nlp
@ -142,12 +142,12 @@ for text_chunk in text_chunks:
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for ent_candidate in token.sent.ents:
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for ent_candidate in token.sent.ents:
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if ent_candidate.start_char == token.idx:
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if ent_candidate.start_char == token.idx:
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ent = ent_candidate
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ent = ent_candidate
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annotation = {'start': ent.start_char + chunk_offset,
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'end': ent.end_char + chunk_offset,
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'tag': 'ent',
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'properties': {'type': token.ent_type_}}
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annotations.append(annotation)
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break
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break
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annotation = {'start': ent.start_char + chunk_offset,
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'end': ent.end_char + chunk_offset,
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'tag': 'ent',
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'properties': {'type': token.ent_type_}}
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annotations.append(annotation)
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annotation = {'start': token.idx + chunk_offset,
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annotation = {'start': token.idx + chunk_offset,
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'end': token.idx + len(token.text) + chunk_offset,
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'end': token.idx + len(token.text) + chunk_offset,
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'tag': 'token',
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'tag': 'token',
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@ -157,7 +157,7 @@ for text_chunk in text_chunks:
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if token.ent_type_:
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if token.ent_type_:
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annotation['properties']['ner'] = token.ent_type_
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annotation['properties']['ner'] = token.ent_type_
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annotations.append(annotation)
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annotations.append(annotation)
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chunk_offset = len(text_chunk)
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chunk_offset += len(text_chunk)
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with open(args.output, 'w') as output_file:
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with open(args.output, 'w') as output_file:
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json.dump({'meta': meta, 'tags': tags, 'annotations': annotations},
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json.dump({'meta': meta, 'tags': tags, 'annotations': annotations},
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