ARAFA: An LLM-Generated Arabic Fact-Checking Dataset
Automatic fact-checking poses a significant challenge in Arabic natural language processing due to the scarcity of datasets and resources. In this manuscript, we introduce Arafa, a new large-scale dataset for fact-checking in Modern Standard Arabic, constructed through an automated framework leveraging large language models (LLMs). The dataset was constructed through a three-step pipeline: (1) claim generation from Arabic Wikipedia pages with supporting textual evidence, (2) claim mutation to generate challenging counterfactual claims with refuting evidence, and (3) an automatic validation step to validate that the generated claims are either supported or refuted by their accompanying evi...
| Authors | Christophe Khalil, Shady Elbassuoni, Rida Assaf |
|---|---|
| Primary category | cs.CL |
| Published | 22 September 2026 |
| Last updated at source | 14 October 2026 |
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