ASTE-Transformer: Modelling Dependencies in Aspect-Sentiment Triplet Extraction

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F24%3A10492890" target="_blank" >RIV/00216208:11320/24:10492890 - isvavai.cz</a>

Result on the web

<a href="https://aclanthology.org/2024.findings-emnlp.129" target="_blank" >https://aclanthology.org/2024.findings-emnlp.129</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

ASTE-Transformer: Modelling Dependencies in Aspect-Sentiment Triplet Extraction

Original language description

Aspect-Sentiment Triplet Extraction (ASTE) is a recently proposed task of aspect-based sentiment analysis that consists in extracting (aspect phrase, opinion phrase, sentiment polarity) triples from a given sentence. Recent state-of-the-art methods approach this task by first extracting all possible text spans from a given text, then filtering the potential aspect and opinion phrases with a classifier, and finally considering all their pairs with another classifier that additionally assigns sentiment polarity to them. Although several variations of the above scheme have been proposed, the common feature is that the final result is constructed by a sequence of independent classifier decisions. This hinders the exploitation of dependencies between extracted phrases and prevents the use of knowledge about the interrelationships between classifier predictions to improve performance. In this paper, we propose a new ASTE approach consisting of three transformer-inspired layers, which enables the modelling o

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Findings of the Association for Computational Linguistics: EMNLP 2024

ISBN

979-8-89176-168-1

ISSN

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e-ISSN

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Number of pages

16

Pages from-to

2324-2339

Publisher name

Association for Computational Linguistics

Place of publication

Kerrville, TX, USA

Event location

Miami, FL, USA

Event date

Nov 12, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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