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{ "pk": 49788, "title": "Modelling compounding across languages with analogy and composition", "subtitle": null, "abstract": "Compounding is a common word formation process in many languages around the world. Previous semantic analyses of compounding suggest that analogy and composition are crucial cognitive processes that underlie the formation of new compounds, but these processes are typically considered separately. Here, we formulate a computational model of compounding that integrates both analogy and composition. Compared to simpler baselines, we show that the model combining both processes achieves the best performance in predicting the constituents of attested compounds in English, Chinese, and German. Our work extends previous semantic-based accounts of compounding via a computational approach that can be evaluated using large-scale crosslinguistic data.", "language": "eng", "license": { "name": "", "short_name": "", "text": null, "url": "" }, "keywords": [ { "word": "Linguistics; Analogy; Semantics of language; Computational Modeling; Cross-linguistic analysis" } ], "section": "Papers with Poster Presentation", "is_remote": true, "remote_url": "https://escholarship.org/uc/item/7k26z883", "frozenauthors": [ { "first_name": "Aotao", "middle_name": "", "last_name": "Xu", "name_suffix": "", "institution": "University of Toronto", "department": "" }, { "first_name": "Charles", "middle_name": "", "last_name": "Kemp", "name_suffix": "", "institution": "University of Melbourne", "department": "" }, { "first_name": "Lea", "middle_name": "", "last_name": "Frermann", "name_suffix": "", "institution": "University of Melbourne", "department": "" }, { "first_name": "Yang", "middle_name": "", "last_name": "Xu", "name_suffix": "", "institution": "University of Toronto", "department": "" } ], "date_submitted": null, "date_accepted": null, "date_published": "2025-01-01T11:00:00-07:00", "render_galley": null, "galleys": [ { "label": "PDF", "type": "pdf", "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49788/galley/37750/download/" } ] }