bigbio/scifact|科学声明验证数据集|文本分类数据集

---
language:
- en
bigbio_language:
- English
license: cc-by-nc-2.0
multilinguality: monolingual
bigbio_license_shortname: CC_BY_NC_2p0
pretty_name: SciFact
homepage: https://scifact.apps.allenai.org/
bigbio_pubmed: False
bigbio_public: True
bigbio_tasks:
- TEXT_PAIRS_CLASSIFICATION
---

# Dataset Card for SciFact

## Dataset Description

- **Homepage:** https://scifact.apps.allenai.org/
- **Pubmed:** False
- **Public:** True
- **Tasks:** TXT2CLASS

### Scifact Corpus Source

SciFact is a dataset of 1.4K expert-written scientific claims paired with evidence-containing abstracts, and annotated with labels and rationales.
This config has abstracts and document ids.

### Scifact Claims Source

{_DESCRIPTION_BASE} This config connects the claims to the evidence and doc ids.

### Scifact Rationale Bigbio Pairs

{_DESCRIPTION_BASE} This task is the following: given a claim and a text span composed of one or more sentences from an abstract, predict a label from ("rationale", "not_rationale") indicating if the span is evidence (can be supporting or refuting) for the claim. This roughly corresponds to the second task outlined in Section 5 of the paper."

### Scifact Labelprediction Bigbio Pairs

{_DESCRIPTION_BASE} This task is the following: given a claim and a text span composed of one or more sentences from an abstract, predict a label from ("SUPPORT", "NOINFO", "CONTRADICT") indicating if the span supports, provides no info, or contradicts the claim. This roughly corresponds to the thrid task outlined in Section 5 of the paper.

## Citation Information

```
@article{wadden2020fact,
author = {David Wadden and Shanchuan Lin and Kyle Lo and Lucy Lu Wang and Madeleine van Zuylen and Arman Cohan and Hannaneh Hajishirzi},
title = {Fact or Fiction: Verifying Scientific Claims},
year = {2020},
address = {Online},
publisher = {Association for Computational Linguistics},
url = {https://aclanthology.org/2020.emnlp-main.609},
doi = {10.18653/v1/2020.emnlp-main.609},
pages = {7534--7550},
biburl = {},
bibsource = {}
}

```

原始信息汇总

数据集概述

基本信息

• 名称: SciFact
• 语言: 英语
• 许可证: CC BY NC 2.0
• 多语言性: 单语种
• 公开状态: 公开
• PubMed链接: 无

数据集内容

• 数据集大小: 包含1.4K专家撰写的科学声明，每个声明均与包含证据的摘要配对，并附有标签和理由。
• 数据结构:
  • SciFact Corpus Source: 包含摘要和文档ID。
  • SciFact Claims Source: 连接声明与证据及文档ID。
  • SciFact Rationale Bigbio Pairs: 任务为判断给定声明和文本跨度（由摘要中的一个或多个句子组成）是否为证据，标签为("rationale", "not_rationale")。
  • SciFact Labelprediction Bigbio Pairs: 任务为判断给定声明和文本跨度是否支持、提供无信息或反驳声明，标签为("SUPPORT", "NOINFO", "CONTRADICT")。

任务类型

• 主要任务: TEXT_PAIRS_CLASSIFICATION
• 具体任务:
  • 判断文本跨度是否为声明的证据。
  • 判断文本跨度对声明的支持、无信息或反驳情况。

引用信息

@article{wadden2020fact, author = {David Wadden and Shanchuan Lin and Kyle Lo and Lucy Lu Wang and Madeleine van Zuylen and Arman Cohan and Hannaneh Hajishirzi}, title = {Fact or Fiction: Verifying Scientific Claims}, year = {2020}, address = {Online}, publisher = {Association for Computational Linguistics}, url = {https://aclanthology.org/2020.emnlp-main.609}, doi = {10.18653/v1/2020.emnlp-main.609}, pages = {7534--7550}, biburl = {}, bibsource = {} }