<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="costa-etal-2016-mapping">
    <titleInfo>
        <title>Mapping and Generating Classifiers using an Open Chinese Ontology</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Luis</namePart>
        <namePart type="given">Morgado</namePart>
        <namePart type="given">Da</namePart>
        <namePart type="family">Costa</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Francis</namePart>
        <namePart type="family">Bond</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Helena</namePart>
        <namePart type="family">Gao</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2016-27–30 jan</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 8th Global WordNet Conference (GWC)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Christiane</namePart>
            <namePart type="family">Fellbaum</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Piek</namePart>
            <namePart type="family">Vossen</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Verginica</namePart>
            <namePart type="given">Barbu</namePart>
            <namePart type="family">Mititelu</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Corina</namePart>
            <namePart type="family">Forascu</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Global Wordnet Association</publisher>
            <place>
                <placeTerm type="text">Bucharest, Romania</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>In languages such as Chinese, classifiers (CLs) play a central role in the quantification of noun-phrases. This can be a problem when generating text from input that does not specify the classifier, as in machine translation (MT) from English to Chinese. Many solutions to this problem rely on dictionaries of noun-CL pairs. However, there is no open large-scale machine-tractable dictionary of noun-CL associations. Many published resources exist, but they tend to focus on how a CL is used (e.g. what kinds of nouns can be used with it, or what features seem to be selected by each CL). In fact, since nouns are open class words, producing an exhaustive definite list of noun-CL associations is not possible, since it would quickly get out of date. Our work tries to address this problem by providing an algorithm for automatic building of a frequency based dictionary of noun-CL pairs, mapped to concepts in the Chinese Open Wordnet (Wang and Bond, 2013), an open machine-tractable dictionary for Chinese. All results will released under an open license.</abstract>
    <identifier type="citekey">costa-etal-2016-mapping</identifier>
    <location>
        <url>https://aclanthology.org/2016.gwc-1.36</url>
    </location>
    <part>
        <date>2016-27–30 jan</date>
        <extent unit="page">
            <start>249</start>
            <end>256</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Mapping and Generating Classifiers using an Open Chinese Ontology
%A Costa, Luis Morgado Da
%A Bond, Francis
%A Gao, Helena
%Y Fellbaum, Christiane
%Y Vossen, Piek
%Y Mititelu, Verginica Barbu
%Y Forascu, Corina
%S Proceedings of the 8th Global WordNet Conference (GWC)
%D 2016
%8 27–30 jan
%I Global Wordnet Association
%C Bucharest, Romania
%F costa-etal-2016-mapping
%X In languages such as Chinese, classifiers (CLs) play a central role in the quantification of noun-phrases. This can be a problem when generating text from input that does not specify the classifier, as in machine translation (MT) from English to Chinese. Many solutions to this problem rely on dictionaries of noun-CL pairs. However, there is no open large-scale machine-tractable dictionary of noun-CL associations. Many published resources exist, but they tend to focus on how a CL is used (e.g. what kinds of nouns can be used with it, or what features seem to be selected by each CL). In fact, since nouns are open class words, producing an exhaustive definite list of noun-CL associations is not possible, since it would quickly get out of date. Our work tries to address this problem by providing an algorithm for automatic building of a frequency based dictionary of noun-CL pairs, mapped to concepts in the Chinese Open Wordnet (Wang and Bond, 2013), an open machine-tractable dictionary for Chinese. All results will released under an open license.
%U https://aclanthology.org/2016.gwc-1.36
%P 249-256

Markdown (Informal)

[Mapping and Generating Classifiers using an Open Chinese Ontology](https://aclanthology.org/2016.gwc-1.36) (Costa et al., GWC 2016)

• Mapping and Generating Classifiers using an Open Chinese Ontology (Costa et al., GWC 2016)

ACL

• Luis Morgado Da Costa, Francis Bond, and Helena Gao. 2016. Mapping and Generating Classifiers using an Open Chinese Ontology. In Proceedings of the 8th Global WordNet Conference (GWC), pages 249–256, Bucharest, Romania. Global Wordnet Association.