基于BI-LSTM+CRF的中文命名实体识别 Pytorch.zip

# ChinsesNER-pytorch ### train setp 1: edit **models/config.yml** embedding_size: 100 hidden_size: 128 model_path: models/ batch_size: 20 dropout: 0.5 tags: - ORG - PER step 2: train python3 main.py train or cn = ChineseNER("train") cn.train() ... epoch [4] |██████ | 154/591 loss 0.46 evaluation ORG recall 1.00 precision 1.00 f1 1.00 -------------------------------------------------- epoch [4] |██████ | 155/591 loss 1.47 evaluation ORG recall 0.92 precision 0.92 f1 0.92 -------------------------------------------------- epoch [4] |██████ | 156/591 loss 0.46 evaluation ORG recall 0.94 precision 1.00 f1 0.97 ### predict python3 main.py predict or cn = ChineseNER("predict") cn.predict() 请输入文本: 海利装饰材料有限公司 [{'start': 0, 'stop': 10, 'word': '海利装饰材料有限公司', 'type': 'ORG'}] ### REFERENCES - [Log-Linear Models, MEMMs, and CRFs](http://www.cs.columbia.edu/~mcollins/crf.pdf) - [Neural Architectures for Named Entity Recognition](https://arxiv.org/pdf/1603.01360.pdf)