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    <titleInfo>
        <title>Neural Boxer at the IWCS Shared Task on DRS Parsing</title>
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    <name type="personal">
        <namePart type="given">Rik</namePart>
        <namePart type="family">van Noord</namePart>
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            <title>Proceedings of the IWCS Shared Task on Semantic Parsing</title>
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        <name type="personal">
            <namePart type="given">Lasha</namePart>
            <namePart type="family">Abzianidze</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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            <namePart type="given">Rik</namePart>
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        <name type="personal">
            <namePart type="given">Hessel</namePart>
            <namePart type="family">Haagsma</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Johan</namePart>
            <namePart type="family">Bos</namePart>
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    <abstract>This paper describes our participation in the shared task of Discourse Representation Structure parsing. It follows the work of Van Noord et al. (2018), who employed a neural sequence-to-sequence model to produce DRSs, also exploiting linguistic information with multiple encoders. We provide a detailed look in the performance of this model and show that (i) the benefit of the linguistic features is evident across a number of experiments which vary the amount of training data and (ii) the model can be improved by applying a number of postprocessing methods to fix ill-formed output. Our model ended up in second place in the competition, with an F-score of 84.5.</abstract>
    <identifier type="citekey">van-noord-2019-neural</identifier>
    <identifier type="doi">10.18653/v1/W19-1204</identifier>
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%0 Conference Proceedings
%T Neural Boxer at the IWCS Shared Task on DRS Parsing
%A van Noord, Rik
%Y Abzianidze, Lasha
%Y van Noord, Rik
%Y Haagsma, Hessel
%Y Bos, Johan
%S Proceedings of the IWCS Shared Task on Semantic Parsing
%D 2019
%8 May
%I Association for Computational Linguistics
%C Gothenburg, Sweden
%F van-noord-2019-neural
%X This paper describes our participation in the shared task of Discourse Representation Structure parsing. It follows the work of Van Noord et al. (2018), who employed a neural sequence-to-sequence model to produce DRSs, also exploiting linguistic information with multiple encoders. We provide a detailed look in the performance of this model and show that (i) the benefit of the linguistic features is evident across a number of experiments which vary the amount of training data and (ii) the model can be improved by applying a number of postprocessing methods to fix ill-formed output. Our model ended up in second place in the competition, with an F-score of 84.5.
%R 10.18653/v1/W19-1204
%U https://aclanthology.org/W19-1204
%U https://doi.org/10.18653/v1/W19-1204

Markdown (Informal)

[Neural Boxer at the IWCS Shared Task on DRS Parsing](https://aclanthology.org/W19-1204) (van Noord, IWCS 2019)

• Neural Boxer at the IWCS Shared Task on DRS Parsing (van Noord, IWCS 2019)

ACL

• Rik van Noord. 2019. Neural Boxer at the IWCS Shared Task on DRS Parsing. In Proceedings of the IWCS Shared Task on Semantic Parsing, Gothenburg, Sweden. Association for Computational Linguistics.