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        <title>Automatic Derivation of Semantic Representations for Thai Serial Verb Constructions: A Grammar-Based Approach</title>
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        <namePart type="given">Vipasha</namePart>
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            <namePart type="given">Xiyan</namePart>
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    <abstract>Deep semantic representations are useful for many NLU tasks (Droganova and Zeman 2019; Schuster and Manning-2016). Manual annotation to build these representations is time-consuming, and so automatic approaches are preferred (Droganova and Zeman 2019; Bender et al. 2015). This paper demonstrates how rich semantic representations can be automatically derived for Thai Serial Verb Constructions (SVCs), where the semantic relationship between component verbs is not immediately clear from the surface forms. I present the first fully-implemented HPSG analysis for Thai SVCs, deriving appropriate semantic representations (MRS; Copestake et al. 2005) from syntactic features, implemented within a DELPH-IN computational grammar (Slayden 2009). This analysis increases verified coverage of SVCs by 73% and decreases ambiguity by 46%. The final grammar can be found at: https://github.com/VipashaB94/ThaiGrammar</abstract>
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%0 Conference Proceedings
%T Automatic Derivation of Semantic Representations for Thai Serial Verb Constructions: A Grammar-Based Approach
%A Bansal, Vipasha
%Y Fu, Xiyan
%Y Fleisig, Eve
%S Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F bansal-2024-automatic
%X Deep semantic representations are useful for many NLU tasks (Droganova and Zeman 2019; Schuster and Manning-2016). Manual annotation to build these representations is time-consuming, and so automatic approaches are preferred (Droganova and Zeman 2019; Bender et al. 2015). This paper demonstrates how rich semantic representations can be automatically derived for Thai Serial Verb Constructions (SVCs), where the semantic relationship between component verbs is not immediately clear from the surface forms. I present the first fully-implemented HPSG analysis for Thai SVCs, deriving appropriate semantic representations (MRS; Copestake et al. 2005) from syntactic features, implemented within a DELPH-IN computational grammar (Slayden 2009). This analysis increases verified coverage of SVCs by 73% and decreases ambiguity by 46%. The final grammar can be found at: https://github.com/VipashaB94/ThaiGrammar
%U https://aclanthology.org/2024.acl-srw.37
%P 422-437

Markdown (Informal)

[Automatic Derivation of Semantic Representations for Thai Serial Verb Constructions: A Grammar-Based Approach](https://aclanthology.org/2024.acl-srw.37) (Bansal, ACL 2024)

• Automatic Derivation of Semantic Representations for Thai Serial Verb Constructions: A Grammar-Based Approach (Bansal, ACL 2024)

ACL

• Vipasha Bansal. 2024. Automatic Derivation of Semantic Representations for Thai Serial Verb Constructions: A Grammar-Based Approach. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop), pages 422–437, Bangkok, Thailand. Association for Computational Linguistics.