{"url":"/dataset/multifc","name":"MultiFC","full_name":null,"description_markdown":"Publicly available dataset of naturally occurring factual claims for the purpose of automatic claim verification. It is collected from 26 fact checking websites in English, paired with textual sources and rich metadata, and labelled for veracity by human expert journalists. \r\n\r\nSource: [MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims](/paper/multifc-a-real-world-multi-domain-dataset-for)","description_withheld":null,"homepage":"http://www.copenlu.com/publication/2019_emnlp_augenstein/","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/multifc-a-real-world-multi-domain-dataset-for","title":"MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims","first_author":"Isabelle Augenstein","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Semantic Textual Similarity","url":"/task/semantic-textual-similarity","datasets_with_task":"/datasets/task/semantic-textual-similarity"},{"name":"Semantic Similarity","url":"/task/semantic-similarity","datasets_with_task":"/datasets/task/semantic-similarity"},{"name":"Learning-To-Rank","url":"/task/learning-to-rank","datasets_with_task":"/datasets/task/learning-to-rank"}],"languages":[],"variants":["MultiFC"],"data_loaders":[],"num_papers_in_archive":21,"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."}