Fact Extraction and Verfication (FEVER) Dataset
Created by Thorne et al. at 2018, the 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., in English language. Containing 185,445 in JSON file format.
Dataset Download
Download Fact Extraction and Verfication (FEVER) dataset in JSON format.
Download Fact Extraction and Verfication (FEVER) dataset
Machine Learning Model
Pre-trained Machine Learning Models for Classification, Fake News Detection Tasks in English Language.
Classification, Fake News Detection Models
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➡️ Get Early Access Paper
Read full original Fact Extraction and Verfication (FEVER) paper.