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https://github.com/guitaowufeng/LR-CNN


https://github.com/guitaowufeng/LR-CNN

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README

        

# LR-CNN

Source codes for paper:
CNN-Based Chinese NER with Lexicon Rethinking

Requirement:
======
Python 3.6
Pytorch 0.4.1

Input format:
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CoNLL format, with each character and its label splited by a whitespace in a line. The "BMES" tag scheme is prefered.

别 O
错 O
过 O
邻 O
近 O
大 B-LOC
鹏 M-LOC
湾 E-LOC
的 O
湿 O
地 O

Pretrain embedding:
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The pretrained embeddings(word embedding, char embedding) are the same with Lattice LSTM(https://github.com/jiesutd/LatticeLSTM)

Run the code:
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1. Download the character embeddings and word embeddings and put them in the `data` folder.
2. To train/test the demo: `sh train.sh` / `sh test.sh`
3. To train/test your own data: modify the 'train.sh' or 'test.sh' file with your file path, and run the shell file.