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        <title>Embedding derived animacy rankings offer insights into the sources of grammatical animacy</title>
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            <title>Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)</title>
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        <name type="personal">
            <namePart type="given">Luis</namePart>
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        <name type="personal">
            <namePart type="given">Alan</namePart>
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    <abstract>In this study, we applied the semantic projection approach to animacy, a feature that has not been previously explored using this method. We compared the relative animacy rankings of nouns denoting animals, humans, objects, and first-, second-, and third-person pronouns, as derived from word embeddings, with rankings derived from human behavioral ratings of animacy and from grammatical patterns. Our results support the semantic projection approach as an effective method for deriving proxies of human perception from word embeddings and offer insights into the sources of grammatical animacy.</abstract>
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    <identifier type="doi">10.18653/v1/2025.naacl-long.62</identifier>
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%0 Conference Proceedings
%T Embedding derived animacy rankings offer insights into the sources of grammatical animacy
%A Li, Vivian G.
%Y Chiruzzo, Luis
%Y Ritter, Alan
%Y Wang, Lu
%S Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
%D 2025
%8 April
%I Association for Computational Linguistics
%C Albuquerque, New Mexico
%@ 979-8-89176-189-6
%F li-2025-embedding
%X In this study, we applied the semantic projection approach to animacy, a feature that has not been previously explored using this method. We compared the relative animacy rankings of nouns denoting animals, humans, objects, and first-, second-, and third-person pronouns, as derived from word embeddings, with rankings derived from human behavioral ratings of animacy and from grammatical patterns. Our results support the semantic projection approach as an effective method for deriving proxies of human perception from word embeddings and offer insights into the sources of grammatical animacy.
%R 10.18653/v1/2025.naacl-long.62
%U https://aclanthology.org/2025.naacl-long.62/
%U https://doi.org/10.18653/v1/2025.naacl-long.62
%P 1339-1351

Markdown (Informal)

[Embedding derived animacy rankings offer insights into the sources of grammatical animacy](https://aclanthology.org/2025.naacl-long.62/) (Li, NAACL 2025)

• Embedding derived animacy rankings offer insights into the sources of grammatical animacy (Li, NAACL 2025)

ACL

• Vivian G. Li. 2025. Embedding derived animacy rankings offer insights into the sources of grammatical animacy. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pages 1339–1351, Albuquerque, New Mexico. Association for Computational Linguistics.