{"url":"/dataset/nyt11-hrl","name":"NYT11-HRL","full_name":null,"description_markdown":"Preprocessed version of NYT11.\r\n\r\nEach relational triple is formatted as follows:\r\n\r\nrtext : relation type\r\nem1 : source entity mention\r\nem2 : target entity mention\r\ntags : the proposed entity annotation scheme for the sentence\r\n0 : $O$ non-entity\r\n1 : $S_I$ inside of a source entity\r\n2 : $T_I$ inside of a target entity\r\n3 : $O_I$ inside of not-concerned entity\r\n4 : $S_B$ begin of a source entity\r\n5 : $T_B$ begin of a target entity\r\n6 : $O_B$ begin of not-concerned entity","description_withheld":null,"homepage":"","introduced_date":"2018-11-09","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-hierarchical-framework-for-relation","title":"A Hierarchical Framework for Relation Extraction with Reinforcement Learning","first_author":"Ryuichi Takanobu","url":null},"license":{"name":"None","url":"http://example.com"},"modalities":[],"tasks":[{"name":"Relation Extraction","url":"/task/relation-extraction","datasets_with_task":"/datasets/task/relation-extraction"}],"languages":[],"variants":["NYT11-HRL"],"data_loaders":[],"num_papers_in_archive":15,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/relation-extraction-on-nyt11-hrl","task":"Relation Extraction","dataset_variant":"NYT11-HRL","rows":12,"metrics":["F1"],"first_row_in_archive_order":{"model":"RERE","paper":"/paper/revisiting-the-negative-data-of-distantly","metrics":{"F1":"56.23"},"code_links":[{"title":"redreamality/RERE-relation-extraction","url":"https://github.com/redreamality/RERE-relation-extraction"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/revisiting-the-negative-data-of-distantly","title":"Revisiting the Negative Data of Distantly Supervised Relation Extraction","date":"2021-05-21","rows_on_this_dataset":3,"code_links":1,"syntology":null},{"paper":"/paper/tplinker-single-stage-joint-extraction-of","title":"TPLinker: Single-stage Joint Extraction of Entities and Relations Through Token Pair Linking","date":"2020-10-26","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/a-novel-hierarchical-binary-tagging-framework","title":"A Novel Cascade Binary Tagging Framework for Relational Triple Extraction","date":"2019-09-07","rows_on_this_dataset":2,"code_links":5,"syntology":null},{"paper":"/paper/a-hierarchical-framework-for-relation","title":"A Hierarchical Framework for Relation Extraction with Reinforcement Learning","date":"2018-11-09","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/extracting-relational-facts-by-an-end-to-end","title":"Extracting Relational Facts by an End-to-End Neural Model with Copy Mechanism","date":"2018-07-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/joint-extraction-of-entities-and-relations","title":"Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme","date":"2017-06-07","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/cotype-joint-extraction-of-typed-entities-and","title":"CoType: Joint Extraction of Typed Entities and Relations with Knowledge Bases","date":"2016-10-27","rows_on_this_dataset":1,"code_links":3,"syntology":null},{"paper":"/paper/end-to-end-relation-extraction-using-lstms-on","title":"End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures","date":"2016-01-05","rows_on_this_dataset":1,"code_links":2,"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."}