vi-core-nlp is a library that supports Vietnamese NER by pattern matching .
Project description
NER for Vietnamese Medical Appointment Chatbot
Usage
Extractor NER
import vi_nlp_core
from vi_nlp_core.ner.extractor import Extractor
extractor = Extractor()
text = 'tôi muốn đặt lịch với bs nguyễn nhật lệ lúc 8h sáng ngày 20/7'
print(extractor.extract_ner(text))
[{'start': 25, 'end': 44, 'entity': 'person_name', 'value': 'Nguyễn Nhật Lệ Lúc ', 'confidence': 1.0, 'extractor': 'pattern'}, {'start': 44, 'end': 46, 'entity': 'time', 'value': (8, 0), 'confidence': 1.0, 'extractor': 'absolute_pattern'}, {'start': 57, 'end': 61, 'entity': 'date_time', 'value': [(None, 20, 7, None)], 'confidence': 1.0, 'extractor': 'date_matcher'}]
Extract person name
text = "tôi cần đặt bác sĩ tạ biên cương"
print(extractor.extract_person_name(text)
{'entities': [{'start': 19, 'end': 32, 'entity': 'person_name', 'value': 'Tạ Biên Cương', 'confidence': 1.0, 'extractor': 'pattern'}]}
Extract Date
text = "tôi sinh vào ngày 21-3-1997"
extractor.extract_date(text)
{'entities': [{'start': 18, 'end': 27, 'entity': 'date_time', 'value': [('thứ 6', 21, 3, 1997)], 'confidence': 1.0, 'extractor': 'date_matcher'}]}
Extract Time
text = '14:50 ngày 7 tháng 6'
print(extractor.extract_time(text,return_value=True)) #return value only
[(14, 50)]
Map department/gender to keys
text = 'rai'
res = extractor.map_gender_to_key(text)
print(res)
# {'key': 'GEN01', 'text': 'rai', 'value': 'trai'}
text = 'tiêu hóa'
res = extractor.map_dep_to_key(text)
print(res)
# {'key': 'SP008', 'text': 'tiêu hóa', 'value': 'tiêu hóa'}
From symptoms to Department
text = ['ho', 'sổ mũi', 'đau họng', 'đau đầu', 'nghẹt mũi']
res = extractor.get_department_from_symptoms(text)
[('SP018', 1.0), ('SP006', 0.6), ('SP009', 0.4)]
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