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Dataset: scifact 🏷
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from datasets import load_dataset dataset = load_dataset("scifact")

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Dataset Card for "scifact"

Table of Contents

Dataset Description

Dataset Summary

SciFact, a dataset of 1.4K expert-written scientific claims paired with evidence-containing abstracts, and annotated with labels and rationales

Supported Tasks

More Information Needed

Languages

More Information Needed

Dataset Structure

We show detailed information for up to 5 configurations of the dataset.

Data Instances

claims

  • Size of downloaded dataset files: 2.72 MB
  • Size of the generated dataset: 0.25 MB
  • Total amount of disk used: 2.97 MB

An example of 'validation' looks as follows.

{
    "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

  • Size of downloaded dataset files: 2.72 MB
  • Size of the generated dataset: 7.63 MB
  • Total amount of disk used: 10.35 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "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."
}

Data Fields

The data fields are the same among all splits.

claims

  • id: a int32 feature.
  • claim: a string feature.
  • evidence_doc_id: a string feature.
  • evidence_label: a string feature.
  • evidence_sentences: a list of int32 features.
  • cited_doc_ids: a list of int32 features.

corpus

  • doc_id: a int32 feature.
  • title: a string feature.
  • abstract: a list of string features.
  • structured: a bool feature.

Data Splits Sample Size

claims

train validation test
claims 1261 450 300

corpus

train
corpus 5183

Dataset Creation

Curation Rationale

More Information Needed

Source Data

More Information Needed

Annotations

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

More Information Needed

Citation Information

@inproceedings{scifact2020
  title={ Fact or Fiction: Verifying Scientific Claims},
  author={David,  Wadden and Kyle, Lo and Lucy Lu, Wang and Shanchuan, Lin and Madeleine van, Zuylen and Arman, Cohan and  Hannaneh, Hajishirzi},
  booktitle={2011 AAAI Spring Symposium Series},
  year={2020},
}