# LR-CNN

**Repository Path**: zzflybird/LR-CNN

## Basic Information

- **Project Name**: LR-CNN
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-08-11
- **Last Updated**: 2022-03-09

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## 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.