{"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/de-conflated-semantic-representations","title":"De-Conflated Semantic Representations","arxiv_id":"1608.01961","date":"2016-08-05","proceeding":"EMNLP 2016 11","authors":["Mohammad Taher Pilehvar","Nigel Collier"],"abstract":"One major deficiency of most semantic representation techniques is that they\nusually model a word type as a single point in the semantic space, hence\nconflating all the meanings that the word can have. Addressing this issue by\nlearning distinct representations for individual meanings of words has been the\nsubject of several research studies in the past few years. However, the\ngenerated sense representations are either not linked to any sense inventory or\nare unreliable for infrequent word senses. We propose a technique that tackles\nthese problems by de-conflating the representations of words based on the deep\nknowledge it derives from a semantic network. Our approach provides multiple\nadvantages in comparison to the past work, including its high coverage and the\nability to generate accurate representations even for infrequent word senses.\nWe carry out evaluations on six datasets across two semantic similarity tasks\nand report state-of-the-art results on most of them.","url_abs":"http://arxiv.org/abs/1608.01961v1","url_pdf":"http://arxiv.org/pdf/1608.01961v1.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":"de-conflated-semantic-representations","repo_url":"https://github.com/pilehvar/deconf","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"semantic-similarity","task_name":"Semantic Similarity"},{"task_slug":"semantic-textual-similarity","task_name":"Semantic Textual Similarity"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}