<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="tseng-hsieh-2019-augmenting">
    <titleInfo>
        <title>Augmenting Chinese WordNet semantic relations with contextualized embeddings</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Yu-Hsiang</namePart>
        <namePart type="family">Tseng</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Shu-Kai</namePart>
        <namePart type="family">Hsieh</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 10th Global Wordnet Conference</title>
        </titleInfo>
        <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">Christiane</namePart>
            <namePart type="family">Fellbaum</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Global Wordnet Association</publisher>
            <place>
                <placeTerm type="text">Wroclaw, Poland</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Constructing semantic relations in WordNet has been a labour-intensive task, especially in a dynamic and fast-changing language environment. Combined with recent advancements of contextualized embeddings, this paper proposes the concept of morphology-guided sense vectors, which can be used to semi-automatically augment semantic relations in Chinese Wordnet (CWN). This paper (1) built sense vectors with pre-trained contextualized embedding models; (2) demonstrated the sense vectors computed were consistent with the sense distinctions made in CWN; and (3) predicted the potential semantically-related sense pairs with high accuracy by sense vectors model.</abstract>
    <identifier type="citekey">tseng-hsieh-2019-augmenting</identifier>
    <location>
        <url>https://aclanthology.org/2019.gwc-1.19/</url>
    </location>
    <part>
        <date>2019-07</date>
        <extent unit="page">
            <start>151</start>
            <end>159</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Augmenting Chinese WordNet semantic relations with contextualized embeddings
%A Tseng, Yu-Hsiang
%A Hsieh, Shu-Kai
%Y Vossen, Piek
%Y Fellbaum, Christiane
%S Proceedings of the 10th Global Wordnet Conference
%D 2019
%8 July
%I Global Wordnet Association
%C Wroclaw, Poland
%F tseng-hsieh-2019-augmenting
%X Constructing semantic relations in WordNet has been a labour-intensive task, especially in a dynamic and fast-changing language environment. Combined with recent advancements of contextualized embeddings, this paper proposes the concept of morphology-guided sense vectors, which can be used to semi-automatically augment semantic relations in Chinese Wordnet (CWN). This paper (1) built sense vectors with pre-trained contextualized embedding models; (2) demonstrated the sense vectors computed were consistent with the sense distinctions made in CWN; and (3) predicted the potential semantically-related sense pairs with high accuracy by sense vectors model.
%U https://aclanthology.org/2019.gwc-1.19/
%P 151-159

Markdown (Informal)

[Augmenting Chinese WordNet semantic relations with contextualized embeddings](https://aclanthology.org/2019.gwc-1.19/) (Tseng & Hsieh, GWC 2019)

• Augmenting Chinese WordNet semantic relations with contextualized embeddings (Tseng & Hsieh, GWC 2019)

ACL

• Yu-Hsiang Tseng and Shu-Kai Hsieh. 2019. Augmenting Chinese WordNet semantic relations with contextualized embeddings. In Proceedings of the 10th Global Wordnet Conference, pages 151–159, Wroclaw, Poland. Global Wordnet Association.