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Dataset: fever 🏷
Update on GitHub

How to load this dataset directly with the πŸ€—/nlp library:

				
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from nlp import load_dataset dataset = load_dataset("fever")

Description

With billions of individual pages on the web providing information on almost every conceivable topic, we should have the ability to collect facts that answer almost every conceivable question. However, only a small fraction of this information is contained in structured sources (Wikidata, Freebase, etc.) – we are therefore limited by our ability to transform free-form text to structured knowledge. There is, however, another problem that has become the focus of a lot of recent research and media coverage: false information coming from unreliable sources. [1] [2] The FEVER workshops are a venue for work in verifiable knowledge extraction and to stimulate progress in this direction.

Citation

@inproceedings{Thorne18Fever,
    author = {Thorne, James and Vlachos, Andreas and Christodoulopoulos, Christos and Mittal, Arpit},
    title = {{FEVER}: a Large-scale Dataset for Fact Extraction and VERification},
    booktitle = {NAACL-HLT},
    year = {2018}
}
}

Models trained or fine-tuned on fever

None yet. Start fine-tuning now =)