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        <title>UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification</title>
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        <namePart type="given">Andreas</namePart>
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    <name type="personal">
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    <name type="personal">
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            <title>Proceedings of the First Workshop on Fact Extraction and VERification (FEVER)</title>
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    <abstract>The Fact Extraction and VERification (FEVER) shared task was launched to support the development of systems able to verify claims by extracting supporting or refuting facts from raw text. The shared task organizers provide a large-scale dataset for the consecutive steps involved in claim verification, in particular, document retrieval, fact extraction, and claim classification. In this paper, we present our claim verification pipeline approach, which, according to the preliminary results, scored third in the shared task, out of 23 competing systems. For the document retrieval, we implemented a new entity linking approach. In order to be able to rank candidate facts and classify a claim on the basis of several selected facts, we introduce two extensions to the Enhanced LSTM (ESIM).</abstract>
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        <date>2018-nov</date>
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%0 Conference Proceedings
%T UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification
%A Hanselowski, Andreas
%A Zhang, Hao
%A Li, Zile
%A Sorokin, Daniil
%A Schiller, Benjamin
%A Schulz, Claudia
%A Gurevych, Iryna
%S Proceedings of the First Workshop on Fact Extraction and VERification (FEVER)
%D 2018
%8 nov
%I Association for Computational Linguistics
%C Brussels, Belgium
%F hanselowski-etal-2018-ukp
%X The Fact Extraction and VERification (FEVER) shared task was launched to support the development of systems able to verify claims by extracting supporting or refuting facts from raw text. The shared task organizers provide a large-scale dataset for the consecutive steps involved in claim verification, in particular, document retrieval, fact extraction, and claim classification. In this paper, we present our claim verification pipeline approach, which, according to the preliminary results, scored third in the shared task, out of 23 competing systems. For the document retrieval, we implemented a new entity linking approach. In order to be able to rank candidate facts and classify a claim on the basis of several selected facts, we introduce two extensions to the Enhanced LSTM (ESIM).
%R 10.18653/v1/W18-5516
%U https://aclanthology.org/W18-5516
%U https://doi.org/10.18653/v1/W18-5516
%P 103-108

Markdown (Informal)

[UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification](https://aclanthology.org/W18-5516) (Hanselowski et al., 2018)

• UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification (Hanselowski et al., 2018)

ACL

• Andreas Hanselowski, Hao Zhang, Zile Li, Daniil Sorokin, Benjamin Schiller, Claudia Schulz, and Iryna Gurevych. 2018. UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification. In Proceedings of the First Workshop on Fact Extraction and VERification (FEVER), pages 103–108, Brussels, Belgium. Association for Computational Linguistics.