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        <title>Uni-DUE Student Team: Tackling fact checking through decomposable attention neural network</title>
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            <title>Proceedings of the First Workshop on Fact Extraction and VERification (FEVER)</title>
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            <namePart type="given">James</namePart>
            <namePart type="family">Thorne</namePart>
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            <namePart type="given">Oana</namePart>
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    <abstract>In this paper we present our system for the FEVER Challenge. The task of this challenge is to verify claims by extracting information from Wikipedia. Our system has two parts. In the first part it performs a search for candidate sentences by treating the claims as query. In the second part it filters out noise from these candidates and uses the remaining ones to decide whether they support or refute or entail not enough information to verify the claim. We show that this system achieves a FEVER score of 0.3927 on the FEVER shared task development data set which is a 25.5% improvement over the baseline score.</abstract>
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%0 Conference Proceedings
%T Uni-DUE Student Team: Tackling fact checking through decomposable attention neural network
%A Kowollik, Jan
%A Aker, Ahmet
%Y Thorne, James
%Y Vlachos, Andreas
%Y Cocarascu, Oana
%Y Christodoulopoulos, Christos
%Y Mittal, Arpit
%S Proceedings of the First Workshop on Fact Extraction and VERification (FEVER)
%D 2018
%8 November
%I Association for Computational Linguistics
%C Brussels, Belgium
%F kowollik-aker-2018-uni
%X In this paper we present our system for the FEVER Challenge. The task of this challenge is to verify claims by extracting information from Wikipedia. Our system has two parts. In the first part it performs a search for candidate sentences by treating the claims as query. In the second part it filters out noise from these candidates and uses the remaining ones to decide whether they support or refute or entail not enough information to verify the claim. We show that this system achieves a FEVER score of 0.3927 on the FEVER shared task development data set which is a 25.5% improvement over the baseline score.
%R 10.18653/v1/W18-5518
%U https://aclanthology.org/W18-5518
%U https://doi.org/10.18653/v1/W18-5518
%P 114-118

Markdown (Informal)

[Uni-DUE Student Team: Tackling fact checking through decomposable attention neural network](https://aclanthology.org/W18-5518) (Kowollik & Aker, EMNLP 2018)

• Uni-DUE Student Team: Tackling fact checking through decomposable attention neural network (Kowollik & Aker, EMNLP 2018)

ACL

• Jan Kowollik and Ahmet Aker. 2018. Uni-DUE Student Team: Tackling fact checking through decomposable attention neural network. In Proceedings of the First Workshop on Fact Extraction and VERification (FEVER), pages 114–118, Brussels, Belgium. Association for Computational Linguistics.