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        <title>Data-Driven Frame-Semantic Parsing with Tree Wrapping Grammar</title>
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        <namePart type="given">Tatiana</namePart>
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            <namePart type="given">Maxime</namePart>
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            <namePart type="given">Ellen</namePart>
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    <abstract>We describe the first experimental results for data-driven semantic parsing with Tree Rewriting Grammars (TRGs) and semantic frames. While several theoretical papers previously discussed approaches for modeling frame semantics in the context of TRGs, this is the first data-driven implementation of such a parser. We experiment with Tree Wrapping Grammar (TWG), a grammar formalism closely related to Tree Adjoining Grammar (TAG), developed for formalizing the typologically inspired linguistic theory of Role and Reference Grammar (RRG). We use a transformer-based multi-task architecture to predict semantic supertags which are then decoded into RRG trees augmented with semantic feature structures. We present experiments for sentences in different genres for English data. We also discuss our compositional semantic analyses using TWG for several linguistic phenomena.</abstract>
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%0 Conference Proceedings
%T Data-Driven Frame-Semantic Parsing with Tree Wrapping Grammar
%A Bladier, Tatiana
%A Kallmeyer, Laura
%A Evang, Kilian
%Y Amblard, Maxime
%Y Breitholtz, Ellen
%S Proceedings of the 15th International Conference on Computational Semantics
%D 2023
%8 June
%I Association for Computational Linguistics
%C Nancy, France
%F bladier-etal-2023-data
%X We describe the first experimental results for data-driven semantic parsing with Tree Rewriting Grammars (TRGs) and semantic frames. While several theoretical papers previously discussed approaches for modeling frame semantics in the context of TRGs, this is the first data-driven implementation of such a parser. We experiment with Tree Wrapping Grammar (TWG), a grammar formalism closely related to Tree Adjoining Grammar (TAG), developed for formalizing the typologically inspired linguistic theory of Role and Reference Grammar (RRG). We use a transformer-based multi-task architecture to predict semantic supertags which are then decoded into RRG trees augmented with semantic feature structures. We present experiments for sentences in different genres for English data. We also discuss our compositional semantic analyses using TWG for several linguistic phenomena.
%U https://aclanthology.org/2023.iwcs-1.22
%P 223-232

Markdown (Informal)

[Data-Driven Frame-Semantic Parsing with Tree Wrapping Grammar](https://aclanthology.org/2023.iwcs-1.22) (Bladier et al., IWCS 2023)

• Data-Driven Frame-Semantic Parsing with Tree Wrapping Grammar (Bladier et al., IWCS 2023)

ACL

• Tatiana Bladier, Laura Kallmeyer, and Kilian Evang. 2023. Data-Driven Frame-Semantic Parsing with Tree Wrapping Grammar. In Proceedings of the 15th International Conference on Computational Semantics, pages 223–232, Nancy, France. Association for Computational Linguistics.