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基于模板的文本纠错;Automatically Mining Error Templates for Grammatical Error Correction

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Error Templates for Grammatical Error Correction

Code for the paper: "Mining Error Templates for Grammatical Error Correction". If you use any part of this work, please cite our paper:

@article{zhang2022templates,
  title={Mining Error Templates for Grammatical Error Correction}, 
  author={Yue Zhang and Haochen Jiang and Zuyi Bao and Bo Zhang and Chen Li and Zhenghua Li},
  journal={arXiv preprint arXiv:2206.11569},
  year={2022}
}

Introduction

Some grammatical error correction (GEC) systems incorporate hand-crafted rules and achieve positive results. However, manually defining rules is time-consuming and laborious. In view of this, we propose a method to automatically mine error templates for GEC.

We have accumulated 1,119 error templates along with their corrective actions for Chinese GEC so far (./templates/zh), and open-source 500 of them at present. Each template conforms to the following form:

A
B
1/2/3

We use the regular expression A.*B to represent a error template, and 1/2/3 denote three corrective actions (delete the left/right/random part). For more details, please kindly refer to our paper.

Requirements

Python >= 3.6

Usage

chmod +x example.sh
./example.sh

Expected output:

Fix 3 errors from 3 sentences.

Contact

If you have any problems, feel free to raise an issue or contact hillzhang1999@qq.com.

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基于模板的文本纠错;Automatically Mining Error Templates for Grammatical Error Correction

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