From Articles to Premises: Building PrimeFacts, an Extraction Methodology and Resource for Fact-Checking Evidence
- URL: http://arxiv.org/abs/2605.06006v1
- Date: Thu, 07 May 2026 10:58:29 GMT
- Title: From Articles to Premises: Building PrimeFacts, an Extraction Methodology and Resource for Fact-Checking Evidence
- Abstract summary: PrimeFacts is a methodology for extracting fine-grained evidence from full fact-checking articles.<n>We compile 13,106 PolitiFact articles with claims, verdicts, and all referenced sources.<n>Our framework rewrites anchor sentences into stand-alone, context-independent premises.
- Score: 27.242475349674155
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Fact-checking articles encode rich supporting evidence and reasoning, yet this evidence remains largely inaccessible to automated verification systems due to unstructured presentation. We introduce PrimeFacts, a methodology and resource for extracting fine-grained evidence from full fact-checking articles. We compile 13,106 PolitiFact articles with claims, verdicts, and all referenced sources, and we identify 49,718 in-article hyperlinks as natural anchors to pinpoint key evidence. Our framework leverages large language models (LLMs) to rewrite these anchor sentences into stand-alone, context-independent premises and investigates the extraction of additional implicit evidence. In evaluations on cross-article evidence retrieval and claim verification, the extracted premises substantially improve performance. Decontextualized evidence yields higher retrievability, achieving up to a 30 percent relative gain in Mean Reciprocal Rank over verbatim sentences, and using the evidence for verdict prediction raises Macro-F1 by 10-20 points over the baseline. These gains are consistent across different verdict granularities (2-class vs. 5-class) and model architectures. A qualitative analysis indicates that the decontextualized premises remain faithful to the original sources. Our work highlights the promise of reusing fact-checkers' evidence for automation and provides a large-scale resource of structured evidence from real-world fact-checks.
Related papers
- HiEviDR-Bench: A Benchmark for Hierarchical Evidence Aggregation in Deep Research [52.87128503345243]
We introduce HiEviDR-Bench, a benchmark for evaluating Hierarchical Evidence Aggregation in Deep Research.<n>HiEviDR-Bench represents each instance with an explicit evidence graph that captures evidence selection, cross-source linking, and aggregation.<n>We develop a traceability-oriented evaluation framework with five dimensions: report quality, evidence traceability, citation accuracy, claim verification, and answer correctness.
arXiv Detail & Related papers (2026-07-27T23:50:46Z) - FactReview: Evidence-Grounded Reviews with Literature Positioning and Execution-Based Claim Verification [57.196748998757954]
We present FactReview, an evidence-grounded reviewing system that combines claim extraction, literature positioning, and execution-based claim verification.<n>Given a submission, FactReview identifies major claims and reported results, retrieves nearby work to clarify the paper's technical position, and, when code is available, executes the released repository.<n>It then produces a concise review and an evidence report that assigns each major claim one of five labels: Supported, Supported by the paper, Partially supported, In conflict, or Inconclusive.
arXiv Detail & Related papers (2026-04-05T11:45:22Z) - Contradiction to Consensus: Dual Perspective, Multi Source Retrieval Based Claim Verification with Source Level Disagreement using LLM [0.17188280334580197]
Claim verification, a.k.a. fact-checking, can help identify potential misinformation.<n>Most automated claim verification systems depend on a single knowledge source.<n>We present a novel system for open-domain claim verification.
arXiv Detail & Related papers (2026-02-21T02:21:31Z) - FactAppeal: Identifying Epistemic Factual Appeals in News Media [1.6822770693792826]
Epistemic Appeal Identification identifies whether factual statements have been anchored by external sources or evidence.<n>We present FactAppeal, a manually annotated dataset of 3,226 English-language news sentences.
arXiv Detail & Related papers (2025-10-12T14:14:54Z) - Unstructured Evidence Attribution for Long Context Query Focused Summarization [53.08341620504465]
We propose to extract unstructured (i.e., spans of any length) evidence in order to acquire more relevant and consistent evidence than in the fixed granularity case.<n>We show how existing systems struggle to copy and properly cite unstructured evidence, which also tends to be "lost-in-the-middle"
arXiv Detail & Related papers (2025-02-20T09:57:42Z) - From Relevance to Utility: Evidence Retrieval with Feedback for Fact Verification [118.03466985807331]
We argue that, rather than relevance, for FV we need to focus on the utility that a claim verifier derives from the retrieved evidence.<n>We introduce the feedback-based evidence retriever(FER) that optimize the evidence retrieval process by incorporating feedback from the claim verifier.
arXiv Detail & Related papers (2023-10-18T02:59:38Z) - Give Me More Details: Improving Fact-Checking with Latent Retrieval [58.706972228039604]
Evidence plays a crucial role in automated fact-checking.
Existing fact-checking systems either assume the evidence sentences are given or use the search snippets returned by the search engine.
We propose to incorporate full text from source documents as evidence and introduce two enriched datasets.
arXiv Detail & Related papers (2023-05-25T15:01:19Z) - Read it Twice: Towards Faithfully Interpretable Fact Verification by
Revisiting Evidence [59.81749318292707]
We propose a fact verification model named ReRead to retrieve evidence and verify claim.
The proposed system is able to achieve significant improvements upon best-reported models under different settings.
arXiv Detail & Related papers (2023-05-02T03:23:14Z) - Graph-based Retrieval for Claim Verification over Cross-Document
Evidence [0.6853165736531939]
We conjecture that a graph-based approach can be beneficial to identify fragmented evidence.
We tested this hypothesis by building, over the whole corpus, a large graph that interconnects text portions by means of mentioned entities.
Our experiments show that leveraging on a graph structure is beneficial in identifying a reasonably small portion of passages related to a claim.
arXiv Detail & Related papers (2021-09-13T14:54:26Z) - AmbiFC: Fact-Checking Ambiguous Claims with Evidence [57.7091560922174]
We present AmbiFC, a fact-checking dataset with 10k claims derived from real-world information needs.
We analyze disagreements arising from ambiguity when comparing claims against evidence in AmbiFC.
We develop models for predicting veracity handling this ambiguity via soft labels.
arXiv Detail & Related papers (2021-04-01T17:40:08Z) - Hierarchical Evidence Set Modeling for Automated Fact Extraction and
Verification [5.836068916903788]
Hierarchical Evidence Set Modeling (HESM) is a framework to extract evidence sets and verify a claim to be supported, refuted or not enough info.
Our experimental results show that HESM outperforms 7 state-of-the-art methods for fact extraction and claim verification.
arXiv Detail & Related papers (2020-10-10T22:27:17Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.