<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="fuyao-etal-2023-self">
    <titleInfo>
        <title>Self Question-answering: Aspect Sentiment Triplet Extraction via a Multi-MRC Framework based on Rethink Mechanism</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Zhang</namePart>
        <namePart type="family">Fuyao</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Zhang</namePart>
        <namePart type="family">Yijia</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Wang</namePart>
        <namePart type="family">Mengyi</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Yang</namePart>
        <namePart type="family">Hong</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Lu</namePart>
        <namePart type="family">Mingyu</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Yang</namePart>
        <namePart type="family">Liang</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2023-08</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <language>
        <languageTerm type="text">English</languageTerm>
        <languageTerm type="code" authority="iso639-2b">eng</languageTerm>
    </language>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 22nd Chinese National Conference on Computational Linguistics</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Maosong</namePart>
            <namePart type="family">Sun</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Bing</namePart>
            <namePart type="family">Qin</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Xipeng</namePart>
            <namePart type="family">Qiu</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Jing</namePart>
            <namePart type="family">Jiang</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Xianpei</namePart>
            <namePart type="family">Han</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Chinese Information Processing Society of China</publisher>
            <place>
                <placeTerm type="text">Harbin, China</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>“The purpose of Aspect Sentiment Triplet Extraction (ASTE) is to extract a triplet, including thetarget or aspect, its associated sentiment, and related opinion terms that explain the underlyingcause of the sentiment. Some recent studies fail to capture the strong interdependence betweenATE and OTE, while others fail to effectively introduce the relationship between aspects andopinions into sentiment classification tasks. To solve these problems, we construct a multi-roundmachine reading comprehension framework based on a rethink mechanism to solve ASTE tasksefficiently. The rethink mechanism allows the framework to model complex relationships be-tween entities, and exclusive classifiers and probability generation algorithms can reduce queryconflicts and unilateral drops in probability. Besides, the multi-round structure can fuse explicitsemantic information flow between aspect, opinion and sentiment. Extensive experiments showthat the proposed model achieves the most advanced effect and can be effectively applied toASTE tasks.”</abstract>
    <identifier type="citekey">fuyao-etal-2023-self</identifier>
    <location>
        <url>https://aclanthology.org/2023.ccl-1.60</url>
    </location>
    <part>
        <date>2023-08</date>
        <extent unit="page">
            <start>701</start>
            <end>712</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Self Question-answering: Aspect Sentiment Triplet Extraction via a Multi-MRC Framework based on Rethink Mechanism
%A Fuyao, Zhang
%A Yijia, Zhang
%A Mengyi, Wang
%A Hong, Yang
%A Mingyu, Lu
%A Liang, Yang
%Y Sun, Maosong
%Y Qin, Bing
%Y Qiu, Xipeng
%Y Jiang, Jing
%Y Han, Xianpei
%S Proceedings of the 22nd Chinese National Conference on Computational Linguistics
%D 2023
%8 August
%I Chinese Information Processing Society of China
%C Harbin, China
%G English
%F fuyao-etal-2023-self
%X “The purpose of Aspect Sentiment Triplet Extraction (ASTE) is to extract a triplet, including thetarget or aspect, its associated sentiment, and related opinion terms that explain the underlyingcause of the sentiment. Some recent studies fail to capture the strong interdependence betweenATE and OTE, while others fail to effectively introduce the relationship between aspects andopinions into sentiment classification tasks. To solve these problems, we construct a multi-roundmachine reading comprehension framework based on a rethink mechanism to solve ASTE tasksefficiently. The rethink mechanism allows the framework to model complex relationships be-tween entities, and exclusive classifiers and probability generation algorithms can reduce queryconflicts and unilateral drops in probability. Besides, the multi-round structure can fuse explicitsemantic information flow between aspect, opinion and sentiment. Extensive experiments showthat the proposed model achieves the most advanced effect and can be effectively applied toASTE tasks.”
%U https://aclanthology.org/2023.ccl-1.60
%P 701-712

Markdown (Informal)

[Self Question-answering: Aspect Sentiment Triplet Extraction via a Multi-MRC Framework based on Rethink Mechanism](https://aclanthology.org/2023.ccl-1.60) (Fuyao et al., CCL 2023)

• Self Question-answering: Aspect Sentiment Triplet Extraction via a Multi-MRC Framework based on Rethink Mechanism (Fuyao et al., CCL 2023)

ACL

• Zhang Fuyao, Zhang Yijia, Wang Mengyi, Yang Hong, Lu Mingyu, and Yang Liang. 2023. Self Question-answering: Aspect Sentiment Triplet Extraction via a Multi-MRC Framework based on Rethink Mechanism. In Proceedings of the 22nd Chinese National Conference on Computational Linguistics, pages 701–712, Harbin, China. Chinese Information Processing Society of China.