<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="lewis-2019-compositional">
    <titleInfo>
        <title>Compositional Hyponymy with Positive Operators</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Martha</namePart>
        <namePart type="family">Lewis</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2019-09</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Ruslan</namePart>
            <namePart type="family">Mitkov</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Galia</namePart>
            <namePart type="family">Angelova</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>INCOMA Ltd.</publisher>
            <place>
                <placeTerm type="text">Varna, Bulgaria</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Language is used to describe concepts, and many of these concepts are hierarchical. Moreover, this hierarchy should be compatible with forming phrases and sentences. We use linear-algebraic methods that allow us to encode words as collections of vectors. The representations we use have an ordering, related to subspace inclusion, which we interpret as modelling hierarchical information. The word representations built can be understood within a compositional distributional semantic framework, providing methods for composing words to form phrase and sentence level representations. We show that the resulting representations give competitive results on both word-level hyponymy and sentence-level entailment datasets.</abstract>
    <identifier type="citekey">lewis-2019-compositional</identifier>
    <identifier type="doi">10.26615/978-954-452-056-4_075</identifier>
    <location>
        <url>https://aclanthology.org/R19-1075</url>
    </location>
    <part>
        <date>2019-09</date>
        <extent unit="page">
            <start>638</start>
            <end>647</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Compositional Hyponymy with Positive Operators
%A Lewis, Martha
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
%D 2019
%8 September
%I INCOMA Ltd.
%C Varna, Bulgaria
%F lewis-2019-compositional
%X Language is used to describe concepts, and many of these concepts are hierarchical. Moreover, this hierarchy should be compatible with forming phrases and sentences. We use linear-algebraic methods that allow us to encode words as collections of vectors. The representations we use have an ordering, related to subspace inclusion, which we interpret as modelling hierarchical information. The word representations built can be understood within a compositional distributional semantic framework, providing methods for composing words to form phrase and sentence level representations. We show that the resulting representations give competitive results on both word-level hyponymy and sentence-level entailment datasets.
%R 10.26615/978-954-452-056-4_075
%U https://aclanthology.org/R19-1075
%U https://doi.org/10.26615/978-954-452-056-4_075
%P 638-647

Markdown (Informal)

[Compositional Hyponymy with Positive Operators](https://aclanthology.org/R19-1075) (Lewis, RANLP 2019)

• Compositional Hyponymy with Positive Operators (Lewis, RANLP 2019)

ACL

• Martha Lewis. 2019. Compositional Hyponymy with Positive Operators. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 638–647, Varna, Bulgaria. INCOMA Ltd..