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SLK-NER

Source code for SEKE 2020 paper "SLK-NER: Exploiting Second-order Lexicon Knowledge for Chinese NER"

Requirements

python == 3.6.10
torch == 1.3.1
numpy == 1.17.4
seqeval == 0.0.12
tqdm == 4.40.0

How to use

Dataset

The original datasets can be found at OntoNotes, Weibo and Resume.

Input format:

BMES tag scheme, with each character its label for one line. Sentences are splited with a null line.

  美   B-LOC  
  国   E-LOC  
  的   O  
  华   B-PER  
  莱   M-PER  
  士   E-PER  
  
  我   O  
  跟   O  
  他   O  
  谈   O  
  笑   O  
  风   O  
  生   O   

Pretrained Embeddings

Character embeddings: chinese_L-12_H-768_A-12
Word embeddings: ctb.50d.vec

Training/Testing

bash run_ner.sh

Citation

@inproceedings{hu2020SLK-NER
author={Dou Hu and Lingwei Wei},
title={SLK-NER: Exploiting Second-order Lexicon Knowledge for Chinese NER},
journal={The 32nd International Conference on Software & Knowledge Engineering},
year={2020}
}

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Source code for SEKE 2020 paper "SLK-NER: Exploiting Second-order Lexicon Knowledge for Chinese NER"

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