{"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/entity-linking-meets-word-sense","title":"Entity Linking meets Word Sense Disambiguation: a Unified Approach","arxiv_id":null,"date":"2014-01-01","proceeding":"TACL 2014 1","authors":["Andrea Moro","Aless Raganato","ro","Roberto Navigli"],"abstract":"Entity Linking (EL) and Word Sense Disambiguation (WSD) both address the lexical ambiguity of language. But while the two tasks are pretty similar, they differ in a fundamental respect: in EL the textual mention can be linked to a named entity which may or may not contain the exact mention, while in WSD there is a perfect match between the word form (better, its lemma) and a suitable word sense. In this paper we present Babelfy, a unified graph-based approach to EL and WSD based on a loose identification of candidate meanings coupled with a densest subgraph heuristic which selects high-coherence semantic interpretations. Our experiments show state-of-the-art performances on both tasks on 6 different datasets, including a multilingual setting. Babelfy is online at http://babelfy.org","url_abs":"https://aclanthology.org/Q14-1019","url_pdf":"https://aclanthology.org/Q14-1019.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":[],"tasks":[{"task_slug":"entity-linking","task_name":"Entity Linking"},{"task_slug":"lemma","task_name":"LEMMA"},{"task_slug":"reading-comprehension","task_name":"Reading Comprehension"},{"task_slug":"word-sense-disambiguation","task_name":"Word Sense Disambiguation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/word-sense-disambiguation-on-knowledge-based","task":"Word Sense Disambiguation","dataset":"Knowledge-based:","model":"Babelfy","rank_in_archive_order":3,"of":6,"metrics":{"All":"65.5","SemEval 2007":"51.6","SemEval 2013":"66.4","SemEval 2015":"**70.3**","Senseval 2":"67.0","Senseval 3":"63.5"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}