{"url":"/dataset/wire57","name":"WiRe57","full_name":null,"description_markdown":"We manually performed the task of Open Information Extraction on 5 short documents, elaborating tentative guidelines for the task, and resulting in a ground truth reference of 347 tuples. [section 1]\r\n\r\nA small corpus of 57 sentences taken from the beginning of 5 documents in English was used as the source text from which to extract tuples. Three documents are Wikipedia articles (Chilly Gonzales, the EM algorithm, and Tokyo) and two are newswire articles (taken from Reuters, hence the Wi-Re name). [section 3.1]","description_withheld":null,"homepage":"https://github.com/rali-udem/WiRe57","introduced_date":"2018-09-24","introduced_date_note":null,"introduced_by":{"paper":"/paper/wire57-a-fine-grained-benchmark-for-open","title":"WiRe57 : A Fine-Grained Benchmark for Open Information Extraction","first_author":"William Léchelle","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Open Information Extraction","url":"/task/open-information-extraction","datasets_with_task":"/datasets/task/open-information-extraction"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["WiRe57"],"data_loaders":[],"num_papers_in_archive":8,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/open-information-extraction-on-wire57","task":"Open Information Extraction","dataset_variant":"WiRe57","rows":18,"metrics":["F1"],"first_row_in_archive_order":{"model":"CIGL-OIE + IGL-CA (OpenIE6)","paper":"/paper/openie6-iterative-grid-labeling-and","metrics":{"F1":"40"},"code_links":[{"title":"dair-iitd/openie6","url":"https://github.com/dair-iitd/openie6"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/openie6-iterative-grid-labeling-and","title":"OpenIE6: Iterative Grid Labeling and Coordination Analysis for Open Information Extraction","date":"2020-10-07","rows_on_this_dataset":11,"code_links":1,"syntology":null},{"paper":"/paper/wire57-a-fine-grained-benchmark-for-open","title":"WiRe57 : A Fine-Grained Benchmark for Open Information Extraction","date":"2018-09-24","rows_on_this_dataset":7,"code_links":1,"syntology":null}],"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."}