<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="derczynski-etal-2016-broad">
    <titleInfo>
        <title>Broad Twitter Corpus: A Diverse Named Entity Recognition Resource</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Leon</namePart>
        <namePart type="family">Derczynski</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Kalina</namePart>
        <namePart type="family">Bontcheva</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Ian</namePart>
        <namePart type="family">Roberts</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2016-12</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Yuji</namePart>
            <namePart type="family">Matsumoto</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Rashmi</namePart>
            <namePart type="family">Prasad</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>The COLING 2016 Organizing Committee</publisher>
            <place>
                <placeTerm type="text">Osaka, Japan</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>One of the main obstacles, hampering method development and comparative evaluation of named entity recognition in social media, is the lack of a sizeable, diverse, high quality annotated corpus, analogous to the CoNLL’2003 news dataset. For instance, the biggest Ritter tweet corpus is only 45,000 tokens – a mere 15% the size of CoNLL’2003. Another major shortcoming is the lack of temporal, geographic, and author diversity. This paper introduces the Broad Twitter Corpus (BTC), which is not only significantly bigger, but sampled across different regions, temporal periods, and types of Twitter users. The gold-standard named entity annotations are made by a combination of NLP experts and crowd workers, which enables us to harness crowd recall while maintaining high quality. We also measure the entity drift observed in our dataset (i.e. how entity representation varies over time), and compare to newswire. The corpus is released openly, including source text and intermediate annotations.</abstract>
    <identifier type="citekey">derczynski-etal-2016-broad</identifier>
    <location>
        <url>https://aclanthology.org/C16-1111</url>
    </location>
    <part>
        <date>2016-12</date>
        <extent unit="page">
            <start>1169</start>
            <end>1179</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Broad Twitter Corpus: A Diverse Named Entity Recognition Resource
%A Derczynski, Leon
%A Bontcheva, Kalina
%A Roberts, Ian
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F derczynski-etal-2016-broad
%X One of the main obstacles, hampering method development and comparative evaluation of named entity recognition in social media, is the lack of a sizeable, diverse, high quality annotated corpus, analogous to the CoNLL’2003 news dataset. For instance, the biggest Ritter tweet corpus is only 45,000 tokens – a mere 15% the size of CoNLL’2003. Another major shortcoming is the lack of temporal, geographic, and author diversity. This paper introduces the Broad Twitter Corpus (BTC), which is not only significantly bigger, but sampled across different regions, temporal periods, and types of Twitter users. The gold-standard named entity annotations are made by a combination of NLP experts and crowd workers, which enables us to harness crowd recall while maintaining high quality. We also measure the entity drift observed in our dataset (i.e. how entity representation varies over time), and compare to newswire. The corpus is released openly, including source text and intermediate annotations.
%U https://aclanthology.org/C16-1111
%P 1169-1179

Markdown (Informal)

[Broad Twitter Corpus: A Diverse Named Entity Recognition Resource](https://aclanthology.org/C16-1111) (Derczynski et al., COLING 2016)

• Broad Twitter Corpus: A Diverse Named Entity Recognition Resource (Derczynski et al., COLING 2016)

ACL

• Leon Derczynski, Kalina Bontcheva, and Ian Roberts. 2016. Broad Twitter Corpus: A Diverse Named Entity Recognition Resource. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 1169–1179, Osaka, Japan. The COLING 2016 Organizing Committee.