<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="ringland-etal-2019-nne">
    <titleInfo>
        <title>NNE: A Dataset for Nested Named Entity Recognition in English Newswire</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Nicky</namePart>
        <namePart type="family">Ringland</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Xiang</namePart>
        <namePart type="family">Dai</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Ben</namePart>
        <namePart type="family">Hachey</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Sarvnaz</namePart>
        <namePart type="family">Karimi</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Cecile</namePart>
        <namePart type="family">Paris</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">James</namePart>
        <namePart type="given">R</namePart>
        <namePart type="family">Curran</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2019-07</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Anna</namePart>
            <namePart type="family">Korhonen</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">David</namePart>
            <namePart type="family">Traum</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Lluís</namePart>
            <namePart type="family">Màrquez</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Florence, Italy</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Named entity recognition (NER) is widely used in natural language processing applications and downstream tasks. However, most NER tools target flat annotation from popular datasets, eschewing the semantic information available in nested entity mentions. We describe NNE—a fine-grained, nested named entity dataset over the full Wall Street Journal portion of the Penn Treebank (PTB). Our annotation comprises 279,795 mentions of 114 entity types with up to 6 layers of nesting. We hope the public release of this large dataset for English newswire will encourage development of new techniques for nested NER.</abstract>
    <identifier type="citekey">ringland-etal-2019-nne</identifier>
    <identifier type="doi">10.18653/v1/P19-1510</identifier>
    <location>
        <url>https://aclanthology.org/P19-1510/</url>
    </location>
    <part>
        <date>2019-07</date>
        <extent unit="page">
            <start>5176</start>
            <end>5181</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T NNE: A Dataset for Nested Named Entity Recognition in English Newswire
%A Ringland, Nicky
%A Dai, Xiang
%A Hachey, Ben
%A Karimi, Sarvnaz
%A Paris, Cecile
%A Curran, James R.
%Y Korhonen, Anna
%Y Traum, David
%Y Màrquez, Lluís
%S Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
%D 2019
%8 July
%I Association for Computational Linguistics
%C Florence, Italy
%F ringland-etal-2019-nne
%X Named entity recognition (NER) is widely used in natural language processing applications and downstream tasks. However, most NER tools target flat annotation from popular datasets, eschewing the semantic information available in nested entity mentions. We describe NNE—a fine-grained, nested named entity dataset over the full Wall Street Journal portion of the Penn Treebank (PTB). Our annotation comprises 279,795 mentions of 114 entity types with up to 6 layers of nesting. We hope the public release of this large dataset for English newswire will encourage development of new techniques for nested NER.
%R 10.18653/v1/P19-1510
%U https://aclanthology.org/P19-1510/
%U https://doi.org/10.18653/v1/P19-1510
%P 5176-5181

Markdown (Informal)

[NNE: A Dataset for Nested Named Entity Recognition in English Newswire](https://aclanthology.org/P19-1510/) (Ringland et al., ACL 2019)

• NNE: A Dataset for Nested Named Entity Recognition in English Newswire (Ringland et al., ACL 2019)

ACL

• Nicky Ringland, Xiang Dai, Ben Hachey, Sarvnaz Karimi, Cecile Paris, and James R. Curran. 2019. NNE: A Dataset for Nested Named Entity Recognition in English Newswire. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 5176–5181, Florence, Italy. Association for Computational Linguistics.