{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/simverb-3500-a-large-scale-evaluation-set-of","title":"SimVerb-3500: A Large-Scale Evaluation Set of Verb Similarity","arxiv_id":"1608.00869","date":"2016-08-02","proceeding":"EMNLP 2016 11","authors":["Daniela Gerz","Ivan Vulić","Felix Hill","Roi Reichart","Anna Korhonen"],"abstract":"Verbs play a critical role in the meaning of sentences, but these ubiquitous\nwords have received little attention in recent distributional semantics\nresearch. We introduce SimVerb-3500, an evaluation resource that provides human\nratings for the similarity of 3,500 verb pairs. SimVerb-3500 covers all normed\nverb types from the USF free-association database, providing at least three\nexamples for every VerbNet class. This broad coverage facilitates detailed\nanalyses of how syntactic and semantic phenomena together influence human\nunderstanding of verb meaning. Further, with significantly larger development\nand test sets than existing benchmarks, SimVerb-3500 enables more robust\nevaluation of representation learning architectures and promotes the\ndevelopment of methods tailored to verbs. We hope that SimVerb-3500 will enable\na richer understanding of the diversity and complexity of verb semantics and\nguide the development of systems that can effectively represent and interpret\nthis meaning.","url_abs":"http://arxiv.org/abs/1608.00869v4","url_pdf":"http://arxiv.org/pdf/1608.00869v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"simverb-3500-a-large-scale-evaluation-set-of","repo_url":"https://github.com/accettullihuber/nlp-tools","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"diversity","task_name":"Diversity"},{"task_slug":"representation-learning","task_name":"Representation Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1608.00869","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}