cswangjiawei / pytorch-ner

This is the implemention of named entity recognition model

NER

   This is the implemention of named entity recogntion model. It includes LSTM, LSTM+char, LSTM+CRF, LSTM+char+CRF, CNN, CNN+char, CNN+CRF, CNN+char+CRF. It shows the influence of character embedding and CRF. And it also shows the performance of LSTM and CNN as feature extractors respectively. The following table shows the experimental results of different models on CoNLL2003 dataset.

Model	F1
LSTM	88.30
LSTM+char	90.07
LSTM+CRF	89.59
LSTM+char+CRF	90.86
CNN	87.95
CNN+char	89.97
CNN+CRF	88.22
CNN+char+CRF	90.22

requirements

• pytorch 1.0
• tensorboardX

reference

• https://github.com/jiesutd/NCRFpp