jeffnyman/scifact

SciFact数据集是一个包含专家撰写的科学声明与包含证据的摘要配对的数据集，并且这些配对数据被标注了标签和理由。数据集的结构包括claims和corpus两部分，分别包含不同的数据字段和分割。数据集的许可证为CC BY-NC 2.0，并且提供了相关的引用信息。

原始信息汇总

数据集概述

数据集描述

• 名称: SciFact
• 概述: 该数据集包含专家撰写的科学声明，与包含证据的摘要配对，并附有标签和理由注释。

数据集结构

数据实例

• claims:

  • 下载文件大小: 2.72 MB

  • 生成数据集大小: 0.25 MB

  • 总磁盘使用: 2.97 MB

  • 示例:

    { "cited_doc_ids": [14717500], "claim": "1,000 genomes project enables mapping of genetic sequence variation consisting of rare variants with larger penetrance effects than common variants.", "evidence_doc_id": "14717500", "evidence_label": "SUPPORT", "evidence_sentences": [2, 5], "id": 3 }

• corpus:

  • 下载文件大小: 2.72 MB

  • 生成数据集大小: 7.63 MB

  • 总磁盘使用: 10.35 MB

  • 示例:

    { "abstract": "["Alterations of the architecture of cerebral white matter in the developing human brain can affect cortical development and res...", "doc_id": 4983, "structured": false, "title": "Microstructural development of human newborn cerebral white matter assessed in vivo by diffusion tensor magnetic resonance imaging." }

数据字段

• claims:
  • id: int32
  • claim: string
  • evidence_doc_id: string
  • evidence_label: string
  • evidence_sentences: list of int32
  • cited_doc_ids: list of int32
• corpus:
  • doc_id: int32
  • title: string
  • abstract: list of string
  • structured: bool

数据分割

• claims:

  	train	validation	test
  claims	1261	450	300

• corpus:

  	train
  corpus	5183

附加信息

• 许可证: SciFact数据集根据CC BY-NC 2.0发布。

• 引用信息:

  @inproceedings{wadden-etal-2020-fact, title = "Fact or Fiction: Verifying Scientific Claims", author = "Wadden, David and Lin, Shanchuan and Lo, Kyle and Wang, Lucy Lu and van Zuylen, Madeleine and Cohan, Arman and Hajishirzi, Hannaneh", booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)", month = nov, 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", }