Datasets:
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---
annotations_creators:
- shibing624
language_creators:
- shibing624
language:
- zh
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<20M
source_datasets:
- https://github.com/shibing624/text2vec
- https://github.com/IceFlameWorm/NLP_Datasets/tree/master/ATEC
- http://icrc.hitsz.edu.cn/info/1037/1162.htm
- http://icrc.hitsz.edu.cn/Article/show/171.html
- https://arxiv.org/abs/1908.11828
- https://github.com/pluto-junzeng/CNSD
task_categories:
- text-classification
task_ids:
- natural-language-inference
- semantic-similarity-scoring
- text-scoring
paperswithcode_id: snli
pretty_name: Stanford Natural Language Inference
---
# Dataset Card for NLI_zh
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Repository:** [Chinese NLI dataset](https://github.com/shibing624/text2vec)
- **Leaderboard:** [NLI_zh leaderboard](https://github.com/shibing624/text2vec) (located on the homepage)
- **Size of downloaded dataset files:** 16 MB
- **Total amount of disk used:** 42 MB
### Dataset Summary
常见中文语义匹配数据集，包含[ATEC](https://github.com/IceFlameWorm/NLP_Datasets/tree/master/ATEC)、[BQ](http://icrc.hitsz.edu.cn/info/1037/1162.htm)、[LCQMC](http://icrc.hitsz.edu.cn/Article/show/171.html)、[PAWSX](https://arxiv.org/abs/1908.11828)、[STS-B](https://github.com/pluto-junzeng/CNSD)共5个任务。
数据源：
- ATEC: https://github.com/IceFlameWorm/NLP_Datasets/tree/master/ATEC
- BQ: http://icrc.hitsz.edu.cn/info/1037/1162.htm
- LCQMC: http://icrc.hitsz.edu.cn/Article/show/171.html
- PAWSX: https://arxiv.org/abs/1908.11828
- STS-B: https://github.com/pluto-junzeng/CNSD
### Supported Tasks and Leaderboards
Supported Tasks: 支持中文文本匹配任务，文本相似度计算等相关任务。
中文匹配任务的结果目前在顶会paper上出现较少，我罗列一个我自己训练的结果：
**Leaderboard:** [NLI_zh leaderboard](https://github.com/shibing624/text2vec)
### Languages
数据集均是简体中文文本。
## Dataset Structure
### Data Instances
An example of 'train' looks as follows.
```
{
"sentence1": "刘诗诗杨幂谁漂亮",
"sentence2": "刘诗诗和杨幂谁漂亮",
"label": 1,
}
{
"sentence1": "汇理财怎么样",
"sentence2": "怎么样去理财",
"label": 0,
}
```
### Data Fields
The data fields are the same among all splits.
- `sentence1`: a `string` feature.
- `sentence2`: a `string` feature.
- `label`: a classification label, with possible values including `similarity` (1), `dissimilarity` (0).
### Data Splits
#### ATEC
```shell
$ wc -l ATEC/*
20000 ATEC/ATEC.test.data
62477 ATEC/ATEC.train.data
20000 ATEC/ATEC.valid.data
102477 total
```
#### BQ
```shell
$ wc -l BQ/*
10000 BQ/BQ.test.data
100000 BQ/BQ.train.data
10000 BQ/BQ.valid.data
120000 total
```
#### LCQMC
```shell
$ wc -l LCQMC/*
12500 LCQMC/LCQMC.test.data
238766 LCQMC/LCQMC.train.data
8802 LCQMC/LCQMC.valid.data
260068 total
```
#### PAWSX
```shell
$ wc -l PAWSX/*
2000 PAWSX/PAWSX.test.data
49401 PAWSX/PAWSX.train.data
2000 PAWSX/PAWSX.valid.data
53401 total
```
#### STS-B
```shell
$ wc -l STS-B/*
1361 STS-B/STS-B.test.data
5231 STS-B/STS-B.train.data
1458 STS-B/STS-B.valid.data
8050 total
```
## Dataset Creation
### Curation Rationale
作为中文NLI(natural langauge inference)数据集，这里把这个数据集上传到huggingface的datasets，方便大家使用。
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
数据集的版权归原作者所有，使用各数据集时请尊重原数据集的版权。
BQ: Jing Chen, Qingcai Chen, Xin Liu, Haijun Yang, Daohe Lu, Buzhou Tang, The BQ Corpus: A Large-scale Domain-specific Chinese Corpus For Sentence Semantic Equivalence Identification EMNLP2018.
### Annotations
#### Annotation process
#### Who are the annotators?
原作者。
### Personal and Sensitive Information
## Considerations for Using the Data
### Social Impact of Dataset
This dataset was developed as a benchmark for evaluating representational systems for text, especially including those induced by representation learning methods, in the task of predicting truth conditions in a given context.
Systems that are successful at such a task may be more successful in modeling semantic representations.
### Discussion of Biases
### Other Known Limitations
## Additional Information
### Dataset Curators
- 苏剑林对文件名称有整理
- 我上传到huggingface的datasets
### Licensing Information
用于学术研究。
The BQ corpus is free to the public for academic research.
### Contributions
Thanks to [@shibing624](https://github.com/shibing624) add this dataset.
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