Polish-ASTE: Aspect-Sentiment Triplet Extraction Datasets for Polish

2025-02-27

International Conference on Language Resources and Evaluation

AI Summary

Aspect-Sentiment-Opinion Triplet Extraction (ASTE) lacks annotated resources for Slavic languages, particularly Polish, which has no publicly available dataset. Method: We introduce the first Polish ASTE dataset, covering two domains—hotels and e-commerce—and strictly adhering to the standard English ASTE format to ensure cross-lingual comparability. The dataset is manually annotated with fine-grained sentiment structures and released under a CC-BY-NC license. Contribution/Results: Using this resource, we conduct the first systematic evaluation of two mainstream ASTE paradigms and two Polish large language models, revealing critical performance bottlenecks of existing methods on Slavic languages. This work fills a key gap in low-resource, fine-grained sentiment analysis for Slavic languages and establishes a benchmark dataset and empirical foundation for future multilingual ASTE research and model development.

Technology Category

• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Application Domains: Humanities & Computational Social Science
• Knowledge Representation and Reasoning: Knowledge Representation Languages

Application Category

• Web Mining and Content Analysis: Sentiment analysis and opinion mining
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

Abstract

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.

Problem

• Lack of ASTE datasets for Slavic languages
• Need for Polish-specific sentiment analysis resources
• Evaluation of ASTE techniques on Polish datasets

Innovation

• Polish ASTE datasets creation
• Combining ASTE with LLMs
• Standardized file format adoption