A Graph-based Verification Framework for Fact-Checking

• URL: http://arxiv.org/abs/2503.07282v1
• Date: Mon, 10 Mar 2025 13:02:29 GMT
• Title: A Graph-based Verification Framework for Fact-Checking
• Authors: Yani Huang, Richong Zhang, Zhijie Nie, Junfan Chen, Xuefeng Zhang,
• Abstract summary: We propose a graph-based framework, GraphFC, for fact-checking.<n>Based on this core idea, we propose a graph-based framework, GraphFC, for fact-checking.
• Score: 25.875698681028794
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Fact-checking plays a crucial role in combating misinformation. Existing methods using large language models (LLMs) for claim decomposition face two key limitations: (1) insufficient decomposition, introducing unnecessary complexity to the verification process, and (2) ambiguity of mentions, leading to incorrect verification results. To address these challenges, we suggest introducing a claim graph consisting of triplets to address the insufficient decomposition problem and reduce mention ambiguity through graph structure. Based on this core idea, we propose a graph-based framework, GraphFC, for fact-checking. The framework features three key components: graph construction, which builds both claim and evidence graphs; graph-guided planning, which prioritizes the triplet verification order; and graph-guided checking, which verifies the triples one by one between claim and evidence graphs. Extensive experiments show that GraphFC enables fine-grained decomposition while resolving referential ambiguities through relational constraints, achieving state-of-the-art performance across three datasets.

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