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        <title>Revisiting Syntax-Based Approach in Negation Scope Resolution</title>
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            <title>Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023)</title>
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    <abstract>Negation scope resolution is the process of detecting the negated part of a sentence. Unlike the syntax-based approach employed in previous research, state-of-the-art methods performed better without the explicit use of syntactic structure. This work revisits the syntax-based approach and re-evaluates the effectiveness of syntactic structure in negation scope resolution. We replace the parser utilized in the prior works with state-of-the-art parsers and modify the syntax-based heuristic rules. The experimental results demonstrate that the simple modifications enhance the performance of the prior syntax-based method to the same level as state-of-the-art end-to-end neural-based methods.</abstract>
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    <identifier type="doi">10.18653/v1/2023.starsem-1.3</identifier>
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%0 Conference Proceedings
%T Revisiting Syntax-Based Approach in Negation Scope Resolution
%A Yoshida, Asahi
%A Kato, Yoshihide
%A Matsubara, Shigeki
%Y Palmer, Alexis
%Y Camacho-collados, Jose
%S Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F yoshida-etal-2023-revisiting
%X Negation scope resolution is the process of detecting the negated part of a sentence. Unlike the syntax-based approach employed in previous research, state-of-the-art methods performed better without the explicit use of syntactic structure. This work revisits the syntax-based approach and re-evaluates the effectiveness of syntactic structure in negation scope resolution. We replace the parser utilized in the prior works with state-of-the-art parsers and modify the syntax-based heuristic rules. The experimental results demonstrate that the simple modifications enhance the performance of the prior syntax-based method to the same level as state-of-the-art end-to-end neural-based methods.
%R 10.18653/v1/2023.starsem-1.3
%U https://aclanthology.org/2023.starsem-1.3
%U https://doi.org/10.18653/v1/2023.starsem-1.3
%P 18-23

Markdown (Informal)

[Revisiting Syntax-Based Approach in Negation Scope Resolution](https://aclanthology.org/2023.starsem-1.3) (Yoshida et al., *SEM 2023)

• Revisiting Syntax-Based Approach in Negation Scope Resolution (Yoshida et al., *SEM 2023)

ACL

• Asahi Yoshida, Yoshihide Kato, and Shigeki Matsubara. 2023. Revisiting Syntax-Based Approach in Negation Scope Resolution. In Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023), pages 18–23, Toronto, Canada. Association for Computational Linguistics.