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Temporal models for Word Sense Disambiguation in historical texts and the COALA project| title | Temporal models for Word Sense Disambiguation in historical texts and the COALA project |
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| start_date | 2026/01/09 |
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| schedule | 11h |
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| online | no |
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| location_info | visioconférence Big Blue Button |
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| summary | Word Sense Disambiguation (WSD) is a crucial task in Natural Language Processing (NLP) that determines the most likely sense of a polysemous word in context. While WSD techniques have seen significant improvements for modern languages, challenges persist for historical and low-resource languages. By incorporating temporal sensitivity into computational approaches, WSD performance can be significantly enhanced.
In this talk I will present my research on WSD algorithms designed for historical corpora. Using historical BERT models trained on a corpus of nineteenth-century English books, and leveraging the Oxford English Dictionary and its Historical Thesaurus for evolving sense representations, I will show how time-sensitive models improve performance. I will also present the project “Computational Corpus Annotation for Quantitative Analysis of Latin Lexical Semantics” (COALA), successfully evaluated as an ERC Consolidator Grant. |
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| responsibles | Bawden |
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Workflow history| from state (1) | to state | comment | date |
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| submitted | published | | 2026/02/11 13:25 UTC |
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