Padia, AnkurFerraro, FrancisFinin, Tim2018-11-132018-11-132018-11-01http://hdl.handle.net/11603/11967http://dx.doi.org/10.18653/v1/W18-5527Proceedings of the First Workshop on Fact Extraction and VerificationWe describe our system used in the 2018 FEVER shared task. The system employed a frame-based information retrieval approach to select Wikipedia sentences providing evidence and used a two-layer multilayer perceptron to classify a claim as correct or not. Our submission achieved a score of 0.3966 on the Evidence F1 metric with accuracy of 44.79%, and FEVER score of 0.2628 F1 points.5 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.Attribution 4.0 InternationalClaimSemantic Webfact verificationnatural language processingLexical ResourcesUMBC Ebiquity Research GroupUMBC Ebiquity Research GroupText