{"url":"/dataset/rte3-fr","name":"RTE3-FR","full_name":null,"description_markdown":"RTE3-FR dataset is the French translation of the Textual Entailment English dataset used in the RTE-3 Challenge (https://nlp.stanford.edu/RTE3-pilot).\r\n\r\nLike its English counterpart, the French RTE-3 dataset is composed of a development set and a test set, each containing 800 T/H pairs.\r\n\r\nThe dataset is annotated for a 3-way task with the following labels: entailment (0), neutral (1), contradiction (2).\r\n\r\nRTE3-FR is available both in XML and TSV format.","description_withheld":null,"homepage":"https://github.com/mskandalis/rte3-french","introduced_date":"2024-05-23","introduced_date_note":null,"introduced_by":{"paper":"/paper/new-datasets-for-automatic-detection-of","title":"New Datasets for Automatic Detection of Textual Entailment and of Contradictions between Sentences in French","first_author":"Maximos Skandalis","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Natural Language Inference","url":"/task/natural-language-inference","datasets_with_task":"/datasets/task/natural-language-inference"},{"name":"RTE","url":"/task/rte","datasets_with_task":"/datasets/task/rte"},{"name":"Sentence-Pair Classification","url":"/task/sentence-pair-classification","datasets_with_task":"/datasets/task/sentence-pair-classification"}],"languages":[{"name":"French","url":"/datasets/language/french"}],"variants":["RTE3-FR"],"data_loaders":[],"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":"2026-09-25T09:33:49+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."}