{"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/improved-word-sense-disambiguation-with","title":"Improved Word Sense Disambiguation with Enhanced Sense Representations","arxiv_id":null,"date":"2021-11-01","proceeding":"Findings (EMNLP) 2021 11","authors":["Yang song","Xin Cai Ong","Hwee Tou Ng","Qian Lin"],"abstract":"Current state-of-the-art supervised word sense disambiguation (WSD) systems (such as GlossBERT and bi-encoder model) yield surprisingly good results by purely leveraging pre-trained language models and short dictionary definitions (or glosses) of the different word senses. While concise and intuitive, the sense gloss is just one of many ways to provide information about word senses. In this paper, we focus on enhancing the sense representations via incorporating synonyms, example phrases or sentences showing usage of word senses, and sense gloss of hypernyms. We show that incorporating such additional information boosts the performance on WSD. With the proposed enhancements, our system achieves an F1 score of 82.0% on the standard benchmark test dataset of the English all-words WSD task, surpassing all previous published scores on this benchmark dataset.","url_abs":"https://aclanthology.org/2021.findings-emnlp.365","url_pdf":"https://aclanthology.org/2021.findings-emnlp.365.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":"improved-word-sense-disambiguation-with","repo_url":"https://github.com/nusnlp/esr","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"GPL-3.0"}}],"tasks":[{"task_slug":"word-sense-disambiguation","task_name":"Word Sense Disambiguation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/word-sense-disambiguation-on-fews","task":"Word Sense Disambiguation","dataset":"FEWS","model":"ESR base","rank_in_archive_order":5,"of":8,"metrics":{"F1 (Fewshot Test)":"77.8","F1 (Zero shot test)":"71.6","F1 (Zeroshot Dev)":"73.9","F1(FewShot Dev)":"77.9"},"uses_additional_data":false},{"leaderboard":"/sota/word-sense-disambiguation-on-fews","task":"Word Sense Disambiguation","dataset":"FEWS","model":"ESR Large","rank_in_archive_order":6,"of":8,"metrics":{"F1 (Fewshot Test)":"83.4","F1 (Zero shot test)":"75.8","F1 (Zeroshot Dev)":"77.4","F1(FewShot Dev)":"83.8"},"uses_additional_data":false},{"leaderboard":"/sota/word-sense-disambiguation-on-supervised","task":"Word Sense Disambiguation","dataset":"Supervised:","model":"ESR+WNGC","rank_in_archive_order":4,"of":27,"metrics":{"SemEval 2007":"78.5","SemEval 2013":"82.3","SemEval 2015":"85.3","Senseval 2":"82.5","Senseval 3":"80.2"},"uses_additional_data":false},{"leaderboard":"/sota/word-sense-disambiguation-on-supervised","task":"Word Sense Disambiguation","dataset":"Supervised:","model":"ESR","rank_in_archive_order":7,"of":27,"metrics":{"SemEval 2007":"77.0","SemEval 2013":"81.5","SemEval 2015":"84.1","Senseval 2":"81.3","Senseval 3":"79.9"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}