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    <titleInfo>
        <title>Sense-specific Historical Word Usage Generation</title>
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        <namePart type="given">Pierluigi</namePart>
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    <abstract>Large-scale sense-annotated corpora are important for a range of tasks but are hard to come by. Dictionaries that record and describe the vocabulary of a language often offer a small set of real-world example sentences for each sense of a word. However, on their own, these sentences are too few to be used as diachronic sense-annotated corpora. We propose a targeted strategy for training and evaluating generative models producing historically and semantically accurate word usages given any word, sense definition, and year triple. Our results demonstrate that fine-tuned models can generate usages with the same properties as real-world example sentences from a reference dictionary. Thus the generated usages will be suitable for training and testing computational models where large-scale sense-annotated corpora are needed but currently unavailable.</abstract>
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    <identifier type="doi">10.1162/tacl_a_00761</identifier>
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        <date>2025</date>
        <detail type="volume"><number>13</number></detail>
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            <start>690</start>
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%0 Journal Article
%T Sense-specific Historical Word Usage Generation
%A Cassotti, Pierluigi
%A Tahmasebi, Nina
%J Transactions of the Association for Computational Linguistics
%D 2025
%V 13
%I MIT Press
%C Cambridge, MA
%F cassotti-tahmasebi-2025-sense
%X Large-scale sense-annotated corpora are important for a range of tasks but are hard to come by. Dictionaries that record and describe the vocabulary of a language often offer a small set of real-world example sentences for each sense of a word. However, on their own, these sentences are too few to be used as diachronic sense-annotated corpora. We propose a targeted strategy for training and evaluating generative models producing historically and semantically accurate word usages given any word, sense definition, and year triple. Our results demonstrate that fine-tuned models can generate usages with the same properties as real-world example sentences from a reference dictionary. Thus the generated usages will be suitable for training and testing computational models where large-scale sense-annotated corpora are needed but currently unavailable.
%R 10.1162/tacl_a_00761
%U https://aclanthology.org/2025.tacl-1.32/
%U https://doi.org/10.1162/tacl_a_00761
%P 690-708

Markdown (Informal)

[Sense-specific Historical Word Usage Generation](https://aclanthology.org/2025.tacl-1.32/) (Cassotti & Tahmasebi, TACL 2025)

• Sense-specific Historical Word Usage Generation (Cassotti & Tahmasebi, TACL 2025)

ACL

• Pierluigi Cassotti and Nina Tahmasebi. 2025. Sense-specific Historical Word Usage Generation. Transactions of the Association for Computational Linguistics, 13:690–708.