{"url":"/dataset/winomt-hindi","name":"WinoMT-Hindi","full_name":null,"description_markdown":"Test set of sentences in Hindi with complex coreference involving two entities inspired by WinoBias format of sentences in English. Includes grammatical gender cues of Hindi to test gender bias in Hindi-English NMT Systems.","description_withheld":null,"homepage":"https://github.com/iampushpdeep/Gender-Bias-Hi-En-Eval/tree/main/WinoMT-Hindi","introduced_date":"2023-11-07","introduced_date_note":null,"introduced_by":{"paper":"/paper/gender-inflected-or-bias-inflicted-on-using","title":"Gender Inflected or Bias Inflicted: On Using Grammatical Gender Cues for Bias Evaluation in Machine Translation","first_author":"Pushpdeep Singh","url":null},"license":{"name":"CC BY","url":"https://creativecommons.org/licenses/by/4.0/"},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[],"languages":[{"name":"Hindi","url":"/datasets/language/hindi"}],"variants":["WinoMT-Hindi"],"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":"2026-09-24T18:15:14+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."}