metadata
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 = {}
}