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    <titleInfo>
        <title>Exploiting Open IE for Deriving Multiple Premises Entailment Corpus</title>
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    <name type="personal">
        <namePart type="given">Martin</namePart>
        <namePart type="family">Víta</namePart>
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    <name type="personal">
        <namePart type="given">Jakub</namePart>
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            <title>Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)</title>
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            <namePart type="given">Ruslan</namePart>
            <namePart type="family">Mitkov</namePart>
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        <name type="personal">
            <namePart type="given">Galia</namePart>
            <namePart type="family">Angelova</namePart>
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    <abstract>Natural language inference (NLI) is a key part of natural language understanding. The NLI task is defined as a decision problem whether a given sentence – hypothesis – can be inferred from a given text. Typically, we deal with a text consisting of just a single premise/single sentence, which is called a single premise entailment (SPE) task. Recently, a derived task of NLI from multiple premises (MPE) was introduced together with the first annotated corpus and corresponding several strong baselines. Nevertheless, the further development in MPE field requires accessibility of huge amounts of annotated data. In this paper we introduce a novel method for rapid deriving of MPE corpora from an existing NLI (SPE) annotated data that does not require any additional annotation work. This proposed approach is based on using an open information extraction system. We demonstrate the application of the method on a well known SNLI corpus. Over the obtained corpus, we provide the first evaluations as well as we state a strong baseline.</abstract>
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    <identifier type="doi">10.26615/978-954-452-056-4_144</identifier>
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        <date>2019-09</date>
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%0 Conference Proceedings
%T Exploiting Open IE for Deriving Multiple Premises Entailment Corpus
%A Víta, Martin
%A Klímek, Jakub
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
%D 2019
%8 September
%I INCOMA Ltd.
%C Varna, Bulgaria
%F vita-klimek-2019-exploiting
%X Natural language inference (NLI) is a key part of natural language understanding. The NLI task is defined as a decision problem whether a given sentence – hypothesis – can be inferred from a given text. Typically, we deal with a text consisting of just a single premise/single sentence, which is called a single premise entailment (SPE) task. Recently, a derived task of NLI from multiple premises (MPE) was introduced together with the first annotated corpus and corresponding several strong baselines. Nevertheless, the further development in MPE field requires accessibility of huge amounts of annotated data. In this paper we introduce a novel method for rapid deriving of MPE corpora from an existing NLI (SPE) annotated data that does not require any additional annotation work. This proposed approach is based on using an open information extraction system. We demonstrate the application of the method on a well known SNLI corpus. Over the obtained corpus, we provide the first evaluations as well as we state a strong baseline.
%R 10.26615/978-954-452-056-4_144
%U https://aclanthology.org/R19-1144
%U https://doi.org/10.26615/978-954-452-056-4_144
%P 1257-1264

Markdown (Informal)

[Exploiting Open IE for Deriving Multiple Premises Entailment Corpus](https://aclanthology.org/R19-1144) (Víta & Klímek, RANLP 2019)

• Exploiting Open IE for Deriving Multiple Premises Entailment Corpus (Víta & Klímek, RANLP 2019)

ACL

• Martin Víta and Jakub Klímek. 2019. Exploiting Open IE for Deriving Multiple Premises Entailment Corpus. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 1257–1264, Varna, Bulgaria. INCOMA Ltd..