<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="kuo-carpuat-2020-evaluating">
    <titleInfo>
        <title>Evaluating a Bi-LSTM Model for Metaphor Detection in TOEFL Essays</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Kevin</namePart>
        <namePart type="family">Kuo</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Marine</namePart>
        <namePart type="family">Carpuat</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2020-07</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the Second Workshop on Figurative Language Processing</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Beata</namePart>
            <namePart type="given">Beigman</namePart>
            <namePart type="family">Klebanov</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Ekaterina</namePart>
            <namePart type="family">Shutova</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Patricia</namePart>
            <namePart type="family">Lichtenstein</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Smaranda</namePart>
            <namePart type="family">Muresan</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Chee</namePart>
            <namePart type="family">Wee</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Anna</namePart>
            <namePart type="family">Feldman</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Debanjan</namePart>
            <namePart type="family">Ghosh</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Online</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>This paper describes systems submitted to the Metaphor Shared Task at the Second Workshop on Figurative Language Processing. In this submission, we replicate the evaluation of the Bi-LSTM model introduced by Gao et al.(2018) on the VUA corpus in a new setting: TOEFL essays written by non-native English speakers. Our results show that Bi-LSTM models outperform feature-rich linear models on this challenging task, which is consistent with prior findings on the VUA dataset. However, the Bi-LSTM models lag behind the best performing systems in the shared task.</abstract>
    <identifier type="citekey">kuo-carpuat-2020-evaluating</identifier>
    <identifier type="doi">10.18653/v1/2020.figlang-1.26</identifier>
    <location>
        <url>https://aclanthology.org/2020.figlang-1.26</url>
    </location>
    <part>
        <date>2020-07</date>
        <extent unit="page">
            <start>192</start>
            <end>196</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Evaluating a Bi-LSTM Model for Metaphor Detection in TOEFL Essays
%A Kuo, Kevin
%A Carpuat, Marine
%Y Klebanov, Beata Beigman
%Y Shutova, Ekaterina
%Y Lichtenstein, Patricia
%Y Muresan, Smaranda
%Y Wee, Chee
%Y Feldman, Anna
%Y Ghosh, Debanjan
%S Proceedings of the Second Workshop on Figurative Language Processing
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F kuo-carpuat-2020-evaluating
%X This paper describes systems submitted to the Metaphor Shared Task at the Second Workshop on Figurative Language Processing. In this submission, we replicate the evaluation of the Bi-LSTM model introduced by Gao et al.(2018) on the VUA corpus in a new setting: TOEFL essays written by non-native English speakers. Our results show that Bi-LSTM models outperform feature-rich linear models on this challenging task, which is consistent with prior findings on the VUA dataset. However, the Bi-LSTM models lag behind the best performing systems in the shared task.
%R 10.18653/v1/2020.figlang-1.26
%U https://aclanthology.org/2020.figlang-1.26
%U https://doi.org/10.18653/v1/2020.figlang-1.26
%P 192-196

Markdown (Informal)

[Evaluating a Bi-LSTM Model for Metaphor Detection in TOEFL Essays](https://aclanthology.org/2020.figlang-1.26) (Kuo & Carpuat, Fig-Lang 2020)

• Evaluating a Bi-LSTM Model for Metaphor Detection in TOEFL Essays (Kuo & Carpuat, Fig-Lang 2020)

ACL

• Kevin Kuo and Marine Carpuat. 2020. Evaluating a Bi-LSTM Model for Metaphor Detection in TOEFL Essays. In Proceedings of the Second Workshop on Figurative Language Processing, pages 192–196, Online. Association for Computational Linguistics.