1.HMM
https://github.com/kifish/NER-demo/tree/hmm
2.CRF
https://github.com/kifish/NER-demo/tree/crf
3.BiLSTM-viterbi
https://github.com/kifish/NER-demo/tree/BiLSTM-viterbi
4.BiLSTM-CRF
https://github.com/kifish/NER-demo/tree/BiLSTM-crf
5.BiLSTM-CNN-CRF
https://github.com/kifish/NER-demo/tree/BiLSTM-cnn-crf
Update:
6.BERT-Softmax
https://github.com/kifish/NER-demo/tree/bert
7.BERT-CRF
https://github.com/kifish/NER-demo/tree/bert
http://nlpprogress.com/english/named_entity_recognition.html
python3.6+ (according to the branch)
pip install -r requirements.txt (according to the branch)
(use pip install git+https://www.github.com/keras-team/keras-contrib.git to install keras-contrib)
precision recall f1-score support
BERT 0.9458 0.9090 0.9263 6195
BERT-CRF 0.9338 0.8901 0.9097 6195
BiLSTM-CRF 0.8616 0.7138 0.7806 6181
BiLSTM-CNN-CRF 0.8406 0.7185 0.7686 6181
CRF 0.8420 0.6279 0.7170 6181
BiLSTM-viterbi 0.8512 0.5700 0.6809 6181
HMM 0.4911 0.4341 0.4479 6181
注: bert做数据预处理的实现和之前的模型不一样, 有一些出入, 导致support有差异, 待对齐。
Todo
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent