{"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/improving-hypernymy-extraction-with","title":"Improving Hypernymy Extraction with Distributional Semantic Classes","arxiv_id":"1711.02918","date":"2017-11-08","proceeding":"LREC 2018 5","authors":["Alexander Panchenko","Dmitry Ustalov","Stefano Faralli","Simone P. Ponzetto","Chris Biemann"],"abstract":"In this paper, we show how distributionally-induced semantic classes can be\nhelpful for extracting hypernyms. We present methods for inducing sense-aware\nsemantic classes using distributional semantics and using these induced\nsemantic classes for filtering noisy hypernymy relations. Denoising of\nhypernyms is performed by labeling each semantic class with its hypernyms. On\nthe one hand, this allows us to filter out wrong extractions using the global\nstructure of distributionally similar senses. On the other hand, we infer\nmissing hypernyms via label propagation to cluster terms. We conduct a\nlarge-scale crowdsourcing study showing that processing of automatically\nextracted hypernyms using our approach improves the quality of the hypernymy\nextraction in terms of both precision and recall. Furthermore, we show the\nutility of our method in the domain taxonomy induction task, achieving the\nstate-of-the-art results on a SemEval'16 task on taxonomy induction.","url_abs":"http://arxiv.org/abs/1711.02918v2","url_pdf":"http://arxiv.org/pdf/1711.02918v2.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":"improving-hypernymy-extraction-with","repo_url":"https://github.com/uhh-lt/mangosteen","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"denoising","task_name":"Denoising"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}