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        <title>Boundary-based MWE segmentation with text partitioning</title>
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        <namePart type="given">Jake</namePart>
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            <title>Proceedings of the 3rd Workshop on Noisy User-generated Text</title>
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            <namePart type="given">Leon</namePart>
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            <namePart type="given">Wei</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Alan</namePart>
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    <abstract>This submission describes the development of a fine-grained, text-chunking algorithm for the task of comprehensive MWE segmentation. This task notably focuses on the identification of colloquial and idiomatic language. The submission also includes a thorough model evaluation in the context of two recent shared tasks, spanning 19 different languages and many text domains, including noisy, user-generated text. Evaluations exhibit the presented model as the best overall for purposes of MWE segmentation, and open-source software is released with the submission (although links are withheld for purposes of anonymity). Additionally, the authors acknowledge the existence of a pre-print document on arxiv.org, which should be avoided to maintain anonymity in review.</abstract>
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%0 Conference Proceedings
%T Boundary-based MWE segmentation with text partitioning
%A Williams, Jake
%Y Derczynski, Leon
%Y Xu, Wei
%Y Ritter, Alan
%Y Baldwin, Tim
%S Proceedings of the 3rd Workshop on Noisy User-generated Text
%D 2017
%8 September
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F williams-2017-boundary
%X This submission describes the development of a fine-grained, text-chunking algorithm for the task of comprehensive MWE segmentation. This task notably focuses on the identification of colloquial and idiomatic language. The submission also includes a thorough model evaluation in the context of two recent shared tasks, spanning 19 different languages and many text domains, including noisy, user-generated text. Evaluations exhibit the presented model as the best overall for purposes of MWE segmentation, and open-source software is released with the submission (although links are withheld for purposes of anonymity). Additionally, the authors acknowledge the existence of a pre-print document on arxiv.org, which should be avoided to maintain anonymity in review.
%R 10.18653/v1/W17-4401
%U https://aclanthology.org/W17-4401
%U https://doi.org/10.18653/v1/W17-4401
%P 1-10

Markdown (Informal)

[Boundary-based MWE segmentation with text partitioning](https://aclanthology.org/W17-4401) (Williams, WNUT 2017)

• Boundary-based MWE segmentation with text partitioning (Williams, WNUT 2017)

ACL

• Jake Williams. 2017. Boundary-based MWE segmentation with text partitioning. In Proceedings of the 3rd Workshop on Noisy User-generated Text, pages 1–10, Copenhagen, Denmark. Association for Computational Linguistics.