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        <title>Robust Document Retrieval and Individual Evidence Modeling for Fact Extraction and Verification.</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>
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    <abstract>This paper presents the ColumbiaNLP submission for the FEVER Workshop Shared Task. Our system is an end-to-end pipeline that extracts factual evidence from Wikipedia and infers a decision about the truthfulness of the claim based on the extracted evidence. Our pipeline achieves significant improvement over the baseline for all the components (Document Retrieval, Sentence Selection and Textual Entailment) both on the development set and the test set. Our team finished 6th out of 24 teams on the leader-board based on the preliminary results with a FEVER score of 49.06 on the blind test set compared to 27.45 of the baseline system.</abstract>
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%0 Conference Proceedings
%T Robust Document Retrieval and Individual Evidence Modeling for Fact Extraction and Verification.
%A Chakrabarty, Tuhin
%A Alhindi, Tariq
%A Muresan, Smaranda
%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 chakrabarty-etal-2018-robust
%X This paper presents the ColumbiaNLP submission for the FEVER Workshop Shared Task. Our system is an end-to-end pipeline that extracts factual evidence from Wikipedia and infers a decision about the truthfulness of the claim based on the extracted evidence. Our pipeline achieves significant improvement over the baseline for all the components (Document Retrieval, Sentence Selection and Textual Entailment) both on the development set and the test set. Our team finished 6th out of 24 teams on the leader-board based on the preliminary results with a FEVER score of 49.06 on the blind test set compared to 27.45 of the baseline system.
%R 10.18653/v1/W18-5521
%U https://aclanthology.org/W18-5521
%U https://doi.org/10.18653/v1/W18-5521
%P 127-131

Markdown (Informal)

[Robust Document Retrieval and Individual Evidence Modeling for Fact Extraction and Verification.](https://aclanthology.org/W18-5521) (Chakrabarty et al., EMNLP 2018)

• Robust Document Retrieval and Individual Evidence Modeling for Fact Extraction and Verification. (Chakrabarty et al., EMNLP 2018)

ACL

• Tuhin Chakrabarty, Tariq Alhindi, and Smaranda Muresan. 2018. Robust Document Retrieval and Individual Evidence Modeling for Fact Extraction and Verification.. In Proceedings of the First Workshop on Fact Extraction and VERification (FEVER), pages 127–131, Brussels, Belgium. Association for Computational Linguistics.