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In this paper we present our system for the FEVER Challenge. The task of thischallenge is to verify claims by extracting information from Wikipedia. Oursystem has two parts. In the first part it performs a search for candidatesentences by treating the claims as query. In the second part it filters outnoise from these candidates and uses the remaining ones to decide whether theysupport or refute or entail not enough information to verify the claim. We showthat this system achieves a FEVER score of 0.3927 on the FEVER shared taskdevelopment data set which is a 25.5% improvement over the baseline score.

Uni-DUE Student Team: Tackling fact checking through decomposable attention neural network