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    <titleInfo>
        <title>Neural Cross-Lingual Transfer and Limited Annotated Data for Named Entity Recognition in Danish</title>
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    <name type="personal">
        <namePart type="given">Barbara</namePart>
        <namePart type="family">Plank</namePart>
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            <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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            <namePart type="given">Barbara</namePart>
            <namePart type="family">Plank</namePart>
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            <publisher>Linköping University Electronic Press</publisher>
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    <abstract>Named Entity Recognition (NER) has greatly advanced by the introduction of deep neural architectures. However, the success of these methods depends on large amounts of training data. The scarcity of publicly-available human-labeled datasets has resulted in limited evaluation of existing NER systems, as is the case for Danish. This paper studies the effectiveness of cross-lingual transfer for Danish, evaluates its complementarity to limited gold data, and sheds light on performance of Danish NER.</abstract>
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        <url>https://aclanthology.org/W19-6143</url>
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        <date>2019-sep–oct</date>
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            <start>370</start>
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%0 Conference Proceedings
%T Neural Cross-Lingual Transfer and Limited Annotated Data for Named Entity Recognition in Danish
%A Plank, Barbara
%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 plank-2019-neural
%X Named Entity Recognition (NER) has greatly advanced by the introduction of deep neural architectures. However, the success of these methods depends on large amounts of training data. The scarcity of publicly-available human-labeled datasets has resulted in limited evaluation of existing NER systems, as is the case for Danish. This paper studies the effectiveness of cross-lingual transfer for Danish, evaluates its complementarity to limited gold data, and sheds light on performance of Danish NER.
%U https://aclanthology.org/W19-6143
%P 370-375

Markdown (Informal)

[Neural Cross-Lingual Transfer and Limited Annotated Data for Named Entity Recognition in Danish](https://aclanthology.org/W19-6143) (Plank, NoDaLiDa 2019)

• Neural Cross-Lingual Transfer and Limited Annotated Data for Named Entity Recognition in Danish (Plank, NoDaLiDa 2019)

ACL

• Barbara Plank. 2019. Neural Cross-Lingual Transfer and Limited Annotated Data for Named Entity Recognition in Danish. In Proceedings of the 22nd Nordic Conference on Computational Linguistics, pages 370–375, Turku, Finland. Linköping University Electronic Press.