{"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-detection-with-an","title":"Improving Hypernymy Detection with an Integrated Path-based and Distributional Method","arxiv_id":"1603.06076","date":"2016-03-19","proceeding":"ACL 2016 8","authors":["Vered Shwartz","Yoav Goldberg","Ido Dagan"],"abstract":"Detecting hypernymy relations is a key task in NLP, which is addressed in the\nliterature using two complementary approaches. Distributional methods, whose\nsupervised variants are the current best performers, and path-based methods,\nwhich received less research attention. We suggest an improved path-based\nalgorithm, in which the dependency paths are encoded using a recurrent neural\nnetwork, that achieves results comparable to distributional methods. We then\nextend the approach to integrate both path-based and distributional signals,\nsignificantly improving upon the state-of-the-art on this task.","url_abs":"http://arxiv.org/abs/1603.06076v3","url_pdf":"http://arxiv.org/pdf/1603.06076v3.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-detection-with-an","repo_url":"https://github.com/vered1986/HypeNET","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1603.06076","atlas_url":"https://app.syntology.ai/?focus=1603.06076","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}