Polish-ASTE: Aspect-Sentiment Triplet Extraction Datasets for Polish
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F24%3A10492877" target="_blank" >RIV/00216208:11320/24:10492877 - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2024.lrec-main.1122/" target="_blank" >https://aclanthology.org/2024.lrec-main.1122/</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Polish-ASTE: Aspect-Sentiment Triplet Extraction Datasets for Polish
Original language description
Aspect-Sentiment Triplet Extraction (ASTE) is one of the most challenging and complex tasks in sentiment analysis. It concerns the construction of triplets that contain an aspect, its associated sentiment polarity, and an opinion phrase that serves as a rationale for the assigned polarity. Despite the growing popularity of the task and the many machine learning methods being proposed to address it, the number of datasets for ASTE is very limited. In particular, no dataset is available for any of the Slavic languages. In this paper, we present two new datasets for ASTE containing customer opinions about hotels and purchased products expressed in Polish. We also perform experiments with two ASTE techniques combined with two large language models for Polish to investigate their performance and the difficulty of the assembled datasets. The new datasets are available under a permissive licence and have the same file format as the English datasets, facilitating their use in future research.
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
2024
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 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
ISBN
978-2-493-81410-4
ISSN
2522-2686
e-ISSN
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Number of pages
8
Pages from-to
12821-12828
Publisher name
European Language Resources Association
Place of publication
Torino, Italy
Event location
Torino, Italy
Event date
May 22, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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