---
license: apache-2.0
language:
- zh
tags:
- text-correction
pretty_name: CSC
task_categories:
- text-generation
---

# Dataset Card for CSC

- **Repository:** https://github.com/shibing624/pycorrector

## Dataset Description

Chinese Spelling Correction (CSC) is a task to detect and correct misspelled characters in Chinese texts. 

CSC is challenging since many Chinese characters are visually or phonologically similar but with quite different semantic meanings.

SIGHAN+Wang271K中文纠错数据集(27万条)，是通过原始SIGHAN13、14、15年数据集和Wang271K数据集格式转化后得到，json格式，带错误字符位置信息，SIGHAN为test.json。


### Original Dataset Summary

- test.json 为 **SIGHAN数据集**， 包括SIGHAN13 14 15，来自 [官方csc.html](http://nlp.ee.ncu.edu.tw/resource/csc.html) ，文件大小：339K，4千条。
- train.json 和 dev.json 为 **Wang271K数据集**，包括 Wang271K ，来自 [Automatic-Corpus-Generation dimmywang提供](https://github.com/wdimmy/Automatic-Corpus-Generation/blob/master/corpus/train.sgml) ，文件大小：93M，27万条。

### Supported Tasks and Leaderboards

The Alpaca dataset designed for instruction training pretrained language models.

### Languages

The data in CSC are in Chinese.

## Dataset Structure

### Data Instances

An example of "train" looks as follows:

```json
{
    "id": "B2-4029-3",
    "original_text": "晚间会听到嗓音，白天的时候大家都不会太在意，但是在睡觉的时候这嗓音成为大家的恶梦。",
    "wrong_ids": [
        5,
        31
    ],
    "correct_text": "晚间会听到噪音，白天的时候大家都不会太在意，但是在睡觉的时候这噪音成为大家的恶梦。"
}
```


### Data Fields

字段解释：
- id：唯一标识符，无意义
- original_text: 原始错误文本
- wrong_ids： 错误字的位置，从0开始
- correct_text: 纠正后的文本

  
### Data Splits

|               | train | dev | test | 
|---------------|------:|--:|--:|
| CSC        | 20万条 | 7万条 | 4千条 |

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset


### Discussion of Biases

[More Information Needed]

### Other Known Limitations

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

The dataset is available under the Apache 2.0.


### Citation Information

```latex
@misc{Xu_Pycorrector_Text_error,
  title={Pycorrector: Text error correction tool},
  author={Xu Ming},
  year={2021},
  howpublished={\url{https://github.com/shibing624/pycorrector}},
}
```

### Contributions

[shibing624](https://github.com/shibing624) 整理并上传