Fact Extraction and Verfication (FEVER)
ClassificationFake News DetectionEnglish
The Fact Extraction and Verfication (FEVER) dataset is a English classification resource from Thorne et al. at 2018 comprising 185,445 examples.
About Fact Extraction and Verfication (FEVER)
Dataset contains 185,445 claims generated by altering sentences extracted from Wikipedia and subsequently verified without knowledge of the sentence they were derived from. The claims are classified as supported, rufted or notenoughinfo.
Details
- Task
- Classification, Fake News Detection
- Language
- English
- Format
- JSON
- Rows / instances
- 185,445
- Creator
- Thorne et al.
- Year
- 2018