def pretty_print(text, tags):
spans = []
for s, e, tag in bio_to_spans(text, tags):
spans.append({"start": s, "end": e, "type": tag})
ents = dict((obj["type"].lower(), obj) for obj in spans).keys()
ret = {
"doc_text": " ".join(text),
"annotation_set": list(ents),
"spans": spans,
"title": "None",
}
print({"doc": ret, "type": "high_level"})
return {"doc": ret, "type": "high_level"}
def pretty_print(text, tags):
spans = []
for s, e, tag in bio_to_spans(text, tags):
spans.append({'start': s, 'end': e, 'type': tag})
ents = dict((obj['type'].lower(), obj) for obj in spans).keys()
ret = {
'doc_text': ' '.join(text),
'annotation_set': list(ents),
'spans': spans,
'title': 'None'
}
print({"doc": ret, 'type': 'high_level'})
return {"doc": ret, 'type': 'high_level'}
def display_results(text_str, predictions, intent_type):
ret = {
"annotation_set": [],
"doc_text": " ".join([t for t in text_str])
}
spans = []
available_tags = set()
for s, e, tag in bio_to_spans(text_str, predictions):
spans.append({"start": s, "end": e, "type": tag})
available_tags.add(tag)
ret["annotation_set"] = list(available_tags)
ret["spans"] = spans
ret["title"] = intent_type
return {"doc": ret, "type": "high_level"}
def display_results(text_str, predictions, intent_type):
ret = {
'annotation_set': [],
'doc_text': ' '.join([t for t in text_str])
}
spans = []
available_tags = set()
for s, e, tag in bio_to_spans(text_str, predictions):
spans.append({'start': s, 'end': e, 'type': tag})
available_tags.add(tag)
ret['annotation_set'] = list(available_tags)
ret['spans'] = spans
ret['title'] = intent_type
return {'doc': ret, 'type': 'high_level'}