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Existing datasets for automated fact-checking have substantial limitations,such as relying on artificial claims, lacking annotations for evidence andintermediate reasoning, or including evidence published after the claim. Inthis paper we introduce AVeriTeC, a new dataset of 4,568 real-world claimscovering fact-checks by 50 different organizations. Each claim is annotatedwith question-answer pairs supported by evidence available online, as well astextual justifications explaining how the evidence combines to produce averdict. Through a multi-round annotation process, we avoid common pitfallsincluding context dependence, evidence insufficiency, and temporal leakage, andreach a substantial inter-annotator agreement of $\kappa=0.619$ on verdicts. Wedevelop a baseline as well as an evaluation scheme for verifying claims throughseveral question-answering steps against the open web.

AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web