<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="ji-eisenstein-2015-one">
    <titleInfo>
        <title>One Vector is Not Enough: Entity-Augmented Distributed Semantics for Discourse Relations</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Yangfeng</namePart>
        <namePart type="family">Ji</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Jacob</namePart>
        <namePart type="family">Eisenstein</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2015</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <genre authority="bibutilsgt">journal article</genre>
    <relatedItem type="host">
        <titleInfo>
            <title>Transactions of the Association for Computational Linguistics</title>
        </titleInfo>
        <originInfo>
            <issuance>continuing</issuance>
            <publisher>MIT Press</publisher>
            <place>
                <placeTerm type="text">Cambridge, MA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">periodical</genre>
        <genre authority="bibutilsgt">academic journal</genre>
    </relatedItem>
    <abstract>Discourse relations bind smaller linguistic units into coherent texts. Automatically identifying discourse relations is difficult, because it requires understanding the semantics of the linked arguments. A more subtle challenge is that it is not enough to represent the meaning of each argument of a discourse relation, because the relation may depend on links between lowerlevel components, such as entity mentions. Our solution computes distributed meaning representations for each discourse argument by composition up the syntactic parse tree. We also perform a downward compositional pass to capture the meaning of coreferent entity mentions. Implicit discourse relations are then predicted from these two representations, obtaining substantial improvements on the Penn Discourse Treebank.</abstract>
    <identifier type="citekey">ji-eisenstein-2015-one</identifier>
    <identifier type="doi">10.1162/tacl_a_00142</identifier>
    <location>
        <url>https://aclanthology.org/Q15-1024</url>
    </location>
    <part>
        <date>2015</date>
        <detail type="volume"><number>3</number></detail>
        <extent unit="page">
            <start>329</start>
            <end>344</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Journal Article
%T One Vector is Not Enough: Entity-Augmented Distributed Semantics for Discourse Relations
%A Ji, Yangfeng
%A Eisenstein, Jacob
%J Transactions of the Association for Computational Linguistics
%D 2015
%V 3
%I MIT Press
%C Cambridge, MA
%F ji-eisenstein-2015-one
%X Discourse relations bind smaller linguistic units into coherent texts. Automatically identifying discourse relations is difficult, because it requires understanding the semantics of the linked arguments. A more subtle challenge is that it is not enough to represent the meaning of each argument of a discourse relation, because the relation may depend on links between lowerlevel components, such as entity mentions. Our solution computes distributed meaning representations for each discourse argument by composition up the syntactic parse tree. We also perform a downward compositional pass to capture the meaning of coreferent entity mentions. Implicit discourse relations are then predicted from these two representations, obtaining substantial improvements on the Penn Discourse Treebank.
%R 10.1162/tacl_a_00142
%U https://aclanthology.org/Q15-1024
%U https://doi.org/10.1162/tacl_a_00142
%P 329-344

Markdown (Informal)

[One Vector is Not Enough: Entity-Augmented Distributed Semantics for Discourse Relations](https://aclanthology.org/Q15-1024) (Ji & Eisenstein, TACL 2015)

• One Vector is Not Enough: Entity-Augmented Distributed Semantics for Discourse Relations (Ji & Eisenstein, TACL 2015)

ACL

• Yangfeng Ji and Jacob Eisenstein. 2015. One Vector is Not Enough: Entity-Augmented Distributed Semantics for Discourse Relations. Transactions of the Association for Computational Linguistics, 3:329–344.