ZHIXIAOBAO at SemEval-2022 Task 10: Apporoaching Structured Sentiment with Graph Parsing
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3AVZ5LWBSI" target="_blank" >RIV/00216208:11320/22:VZ5LWBSI - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2022.semeval-1.187" target="_blank" >https://aclanthology.org/2022.semeval-1.187</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.18653/v1/2022.semeval-1.187" target="_blank" >10.18653/v1/2022.semeval-1.187</a>
Alternative languages
Result language
angličtina
Original language name
ZHIXIAOBAO at SemEval-2022 Task 10: Apporoaching Structured Sentiment with Graph Parsing
Original language description
This paper presents our submission to task 10, Structured Sentiment Analysis of the SemEval 2022 competition. The task aims to extract all elements of the fine-grained sentiment in a text. We cast structured sentiment analysis to the prediction of the sentiment graphs following (Barnes et al., 2021), where nodes are spans of sentiment holders, targets and expressions, and directed edges denote the relation types between them. Our approach closely follows that of semantic dependency parsing (Dozat and Manning, 2018). The difference is that we use pre-trained language models (e.g., BERT and RoBERTa) as text encoder to solve the problem of limited annotated data. Additionally, we make improvements on the computation of cross attention and present the suffix masking technique to make further performance improvement. Substantially, our model achieved the Top-1 average Sentiment Graph F1 score on seven datasets in five different languages in the monolingual subtask.
Czech name
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Czech description
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Classification
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)
Result continuities
Project
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Continuities
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Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
ISBN
978-1-955917-80-3
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
1343-1348
Publisher name
Association for Computational Linguistics
Place of publication
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Event location
Seattle, United States
Event date
Jan 1, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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