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    <titleInfo>
        <title>Docria: Processing and Storing Linguistic Data with Wikipedia</title>
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    <name type="personal">
        <namePart type="given">Marcus</namePart>
        <namePart type="family">Klang</namePart>
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    <name type="personal">
        <namePart type="given">Pierre</namePart>
        <namePart type="family">Nugues</namePart>
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    <originInfo>
        <dateIssued>2019-sep–oct</dateIssued>
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        <titleInfo>
            <title>Proceedings of the 22nd Nordic Conference on Computational Linguistics</title>
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        <name type="personal">
            <namePart type="given">Mareike</namePart>
            <namePart type="family">Hartmann</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Barbara</namePart>
            <namePart type="family">Plank</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <originInfo>
            <publisher>Linköping University Electronic Press</publisher>
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                <placeTerm type="text">Turku, Finland</placeTerm>
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    <abstract>The availability of user-generated content has increased significantly over time. Wikipedia is one example of a corpora which spans a huge range of topics and is freely available. Storing and processing these corpora requires flexible documents models as they may contain malicious and incorrect data. Docria is a library which attempts to address this issue by providing a solution which can be used with small to large corpora, from laptops using Python interactively in a Jupyter notebook to clusters running map-reduce frameworks with optimized compiled code. Docria is available as open-source code.</abstract>
    <identifier type="citekey">klang-nugues-2019-docria</identifier>
    <location>
        <url>https://aclanthology.org/W19-6148</url>
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    <part>
        <date>2019-sep–oct</date>
        <extent unit="page">
            <start>400</start>
            <end>405</end>
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%0 Conference Proceedings
%T Docria: Processing and Storing Linguistic Data with Wikipedia
%A Klang, Marcus
%A Nugues, Pierre
%Y Hartmann, Mareike
%Y Plank, Barbara
%S Proceedings of the 22nd Nordic Conference on Computational Linguistics
%D 2019
%8 sep–oct
%I Linköping University Electronic Press
%C Turku, Finland
%F klang-nugues-2019-docria
%X The availability of user-generated content has increased significantly over time. Wikipedia is one example of a corpora which spans a huge range of topics and is freely available. Storing and processing these corpora requires flexible documents models as they may contain malicious and incorrect data. Docria is a library which attempts to address this issue by providing a solution which can be used with small to large corpora, from laptops using Python interactively in a Jupyter notebook to clusters running map-reduce frameworks with optimized compiled code. Docria is available as open-source code.
%U https://aclanthology.org/W19-6148
%P 400-405

Markdown (Informal)

[Docria: Processing and Storing Linguistic Data with Wikipedia](https://aclanthology.org/W19-6148) (Klang & Nugues, NoDaLiDa 2019)

• Docria: Processing and Storing Linguistic Data with Wikipedia (Klang & Nugues, NoDaLiDa 2019)

ACL

• Marcus Klang and Pierre Nugues. 2019. Docria: Processing and Storing Linguistic Data with Wikipedia. In Proceedings of the 22nd Nordic Conference on Computational Linguistics, pages 400–405, Turku, Finland. Linköping University Electronic Press.