{"url":"/dataset/steusle","name":"STREUSLE","full_name":null,"description_markdown":"STREUSLE stands for Supersense-Tagged Repository of English with a Unified Semantics for Lexical Expressions. The text is from the web reviews portion of the English Web Treebank [9]. STREUSLE incorporates comprehensive annotations of multiword expressions (MWEs) [1] and semantic supersenses for lexical expressions. The supersense labels apply to single- and multiword noun and verb expressions, as described in [2], and prepositional/possessive expressions, as described in [3, 4, 5, 6, 7, 8]. Lexical expressions also feature a lexical category label indicating its holistic grammatical status; for verbal multiword expressions, these labels incorporate categories from the PARSEME 1.1 guidelines [15]. For each token, these pieces of information are concatenated together into a lextag: a sentence's words and their lextags are sufficient to recover lexical categories, supersenses, and multiword expressions [8].","description_withheld":null,"homepage":"https://github.com/nert-nlp/streusle/","introduced_date":"2015-05-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-corpus-and-model-integrating-multiword","title":"A Corpus and Model Integrating Multiword Expressions and Supersenses","first_author":"Noah A. Smith","url":null},"license":{"name":"CC-BY-SA 4.0","url":null},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Natural Language Understanding","url":"/task/natural-language-understanding","datasets_with_task":"/datasets/task/natural-language-understanding"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["STREUSLE"],"data_loaders":[],"num_papers_in_archive":21,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/natural-language-understanding-on-streusle","task":"Natural Language Understanding","dataset_variant":"STREUSLE","rows":11,"metrics":["Tags (Full) Acc","Role F1 (Preps)","Function F1 (Preps)","Full F1 (Preps)"],"first_row_in_archive_order":{"model":"BERT (pred POS/lemmas)","paper":"/paper/lexical-semantic-recognition","metrics":{"Full F1 (Preps)":"71.6","Function F1 (Preps)":"82.8","Role F1 (Preps)":"72.4","Tags (Full) Acc":"82.5"},"code_links":[{"title":"nert-nlp/streusle","url":"https://github.com/nert-nlp/streusle"},{"title":"nelson-liu/lexical-semantic-recognition","url":"https://github.com/nelson-liu/lexical-semantic-recognition"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/lexical-semantic-recognition","title":"Lexical Semantic Recognition","date":"2020-04-30","rows_on_this_dataset":6,"code_links":2,"syntology":null},{"paper":"/paper/comprehensive-supersense-disambiguation-of","title":"Comprehensive Supersense Disambiguation of English Prepositions and Possessives","date":"2018-05-13","rows_on_this_dataset":4,"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."}