Datasets:

shibing624
/

nli_zh

	---
	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.