{"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/sandwich-semantical-analysis-of-neighbours","title":"SANDWiCH: Semantical Analysis of Neighbours for Disambiguating Words in Context ad Hoc","arxiv_id":"2503.05958","date":"2025-03-07","proceeding":null,"authors":["Daniel Guzman-Olivares","Lara Quijano-Sanchez","Federico Liberatore"],"abstract":"The rise of generative chat-based Large Language Models (LLMs) over the past two years has spurred a race to develop systems that promise near-human conversational and reasoning experiences. However, recent studies indicate that the language understanding offered by these models remains limited and far from human-like performance, particularly in grasping the contextual meanings of words, an essential aspect of reasoning. In this paper, we present a simple yet computationally efficient framework for multilingual Word Sense Disambiguation (WSD). Our approach reframes the WSD task as a cluster discrimination analysis over a semantic network refined from BabelNet using group algebra. We validate our methodology across multiple WSD benchmarks, achieving a new state of the art for all languages and tasks, as well as in individual assessments by part of speech. Notably, our model significantly surpasses the performance of current alternatives, even in low-resource languages, while reducing the parameter count by 72%.","url_abs":"https://arxiv.org/abs/2503.05958v1","url_pdf":"https://arxiv.org/pdf/2503.05958v1.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":"sandwich-semantical-analysis-of-neighbours","repo_url":"https://github.com/danielguzmanolivares/sandwich","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"word-sense-disambiguation","task_name":"Word Sense Disambiguation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/word-sense-disambiguation-on-supervised","task":"Word Sense Disambiguation","dataset":"Supervised:","model":"SANDWiCH","rank_in_archive_order":1,"of":27,"metrics":{"SemEval 2007":"80.9","SemEval 2013":"92.6","SemEval 2015":"91.5","Senseval 2":"87.8","Senseval 3":"85.7"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2503.05958","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2503.05958"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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