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中文自然语言的实体抽取和意图识别（Natural Language Understanding），可选Bi-LSTM + CRF 或者 IDCNN + CRF

Python 100.00%
nlu slot slot-filling ner nlp bi-lstm crf idcnn medicle emr

ner-slot_filling's Introduction

NLU项目

这个项目做得是实体的抽取和意图的分类，slot filling and intent classify

语料的处理

python gen_cooked_corpus_and_w2v.py

以上生成模型需要的语料，按1:2:13分别生成test数据、dev数据、train数据。以及用gensim生成词向量，这个可以在更大的语料中训练

训练

python train_evaluate.py --clean True --train True --model_type bilstm

上面用的是bilstm训练，也可以选择使用idcnn。

测试

python train_evaluate.py --train False

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