{"url":"/dataset/hyperred","name":"HyperRED","full_name":"Hyper-Relational Extraction Dataset","description_markdown":"HyperRED is a dataset for the new task of hyper-relational extraction, which extracts relation triplets together with qualifier information such as time, quantity or location. For example, the relation triplet (Leonard Parker, Educated At, Harvard University) can be factually enriched by including the qualifier (End Time, 1967). HyperRED contains 44k sentences with 62 relation types and 44 qualifier types.","description_withheld":null,"homepage":"https://github.com/declare-lab/HyperRED","introduced_date":"2022-11-18","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-dataset-for-hyper-relational-extraction-and","title":"A Dataset for Hyper-Relational Extraction and a Cube-Filling Approach","first_author":"Yew Ken Chia","url":null},"license":{"name":"cc-by-sa-3.0","url":null},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Relation Extraction","url":"/task/relation-extraction","datasets_with_task":"/datasets/task/relation-extraction"},{"name":"Hyper-Relational Extraction","url":"/task/hyper-relational-extraction","datasets_with_task":"/datasets/task/hyper-relational-extraction"},{"name":"Event-based N-ary Relaiton Extraction","url":"/task/event-based-n-ary-relaiton-extraction","datasets_with_task":"/datasets/task/event-based-n-ary-relaiton-extraction"},{"name":"Role-based N-ary Relaiton Extraction","url":"/task/role-based-n-ary-relaiton-extraction","datasets_with_task":"/datasets/task/role-based-n-ary-relaiton-extraction"},{"name":"Hypergraph-based N-ary Relaiton Extraction","url":"/task/hypergraph-based-n-ary-relaiton-extraction","datasets_with_task":"/datasets/task/hypergraph-based-n-ary-relaiton-extraction"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["HyperRED"],"data_loaders":[],"num_papers_in_archive":7,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/hyper-relational-extraction-on-hyperred","task":"Hyper-Relational Extraction","dataset_variant":"HyperRED","rows":4,"metrics":["Avg. F1"],"first_row_in_archive_order":{"model":"Text2NKG","paper":"/paper/text2nkg-fine-grained-n-ary-relation","metrics":{"Avg. F1":"83.81"},"code_links":[{"title":"lhrlab/text2nkg","url":"https://github.com/lhrlab/text2nkg"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/text2nkg-fine-grained-n-ary-relation","title":"Text2NKG: Fine-Grained N-ary Relation Extraction for N-ary relational Knowledge Graph Construction","date":"2023-10-08","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":12,"samples_ran":7,"samples_unverified":5,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/a-dataset-for-hyper-relational-extraction-and","title":"A Dataset for Hyper-Relational Extraction and a Cube-Filling Approach","date":"2022-11-18","rows_on_this_dataset":3,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":12,"samples_ran":7,"samples_unverified":5,"pointer_only_for_licence":1,"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."}