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    <abstract>We propose a novel paradigm for automatic fact-checking that leverages frame semantics to enhance the structured understanding of claims and guide the process of fact-checking them. To support this, we introduce a pilot dataset of real-world claims extracted from PolitiFact, specifically annotated for large-scale structured data. This dataset underpins two case studies: the first investigates voting-related claims using the Vote semantic frame, while the second explores various semantic frames based on data sources from the Organisation for Economic Co-operation and Development (OECD). Our findings demonstrate the effectiveness of frame semantics in improving evidence retrieval and explainability for fact-checking. Finally, we conducted a survey of frames evoked in fact-checked claims, identifying high-impact frames to guide future work in this direction.</abstract>
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%0 Conference Proceedings
%T Task-Oriented Automatic Fact-Checking with Frame-Semantics
%A Devasier, Jacob
%A Putta, Akshith Reddy
%A Mediratta, Rishabh
%A Li, Chengkai
%Y Che, Wanxiang
%Y Nabende, Joyce
%Y Shutova, Ekaterina
%Y Pilehvar, Mohammad Taher
%S Findings of the Association for Computational Linguistics: ACL 2025
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-256-5
%F devasier-etal-2025-task
%X We propose a novel paradigm for automatic fact-checking that leverages frame semantics to enhance the structured understanding of claims and guide the process of fact-checking them. To support this, we introduce a pilot dataset of real-world claims extracted from PolitiFact, specifically annotated for large-scale structured data. This dataset underpins two case studies: the first investigates voting-related claims using the Vote semantic frame, while the second explores various semantic frames based on data sources from the Organisation for Economic Co-operation and Development (OECD). Our findings demonstrate the effectiveness of frame semantics in improving evidence retrieval and explainability for fact-checking. Finally, we conducted a survey of frames evoked in fact-checked claims, identifying high-impact frames to guide future work in this direction.
%R 10.18653/v1/2025.findings-acl.711
%U https://aclanthology.org/2025.findings-acl.711/
%U https://doi.org/10.18653/v1/2025.findings-acl.711
%P 13825-13842

Markdown (Informal)

[Task-Oriented Automatic Fact-Checking with Frame-Semantics](https://aclanthology.org/2025.findings-acl.711/) (Devasier et al., Findings 2025)

• Task-Oriented Automatic Fact-Checking with Frame-Semantics (Devasier et al., Findings 2025)

ACL

• Jacob Devasier, Akshith Reddy Putta, Rishabh Mediratta, and Chengkai Li. 2025. Task-Oriented Automatic Fact-Checking with Frame-Semantics. In Findings of the Association for Computational Linguistics: ACL 2025, pages 13825–13842, Vienna, Austria. Association for Computational Linguistics.