{"url":"/dataset/ficle","name":"FICLE","full_name":"Factual Inconsistency CLassification with Explanation","description_markdown":"The FICLE dataset is a derivative of the FEVER dataset, which is a collection of 185,445 claims generated by modifying sentences obtained from Wikipedia. These claims were then verified without knowledge of the original sentences they were derived from. Each sample in the FEVER dataset consists of a claim sentence, a context sentence extracted from a Wikipedia URL as evidence, and a type label indicating whether the claim is supported, refuted, or lacks sufficient information.","description_withheld":null,"homepage":"https://huggingface.co/datasets/tathagataraha/ficle","introduced_date":"2023-06-15","introduced_date_note":null,"introduced_by":{"paper":"/paper/neural-models-for-factual-inconsistency","title":"Neural models for Factual Inconsistency Classification with Explanations","first_author":"Tathagata Raha","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["FICLE"],"data_loaders":[{"repo":"https://github.com/blitzprecision/ficle","url":"https://huggingface.co/datasets/tathagataraha/ficle","frameworks":["pytorch"]}],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}