Developing PUGG for Polish: A Modern Approach to KBQA, MRC, and IR Dataset Construction

Albert Sawczyn, Katsiaryna Viarenich, Konrad Wojtasik, Aleksandra Domogała, Marcin Oleksy, Maciej Piasecki, Tomasz Kajdanowicz


Abstract
Advancements in AI and natural language processing have revolutionized machine-human language interactions, with question answering (QA) systems playing a pivotal role. The knowledge base question answering (KBQA) task, utilizing structured knowledge graphs (KG), allows for handling extensive knowledge-intensive questions. However, a significant gap exists in KBQA datasets, especially for low-resource languages. Many existing construction pipelines for these datasets are outdated and inefficient in human labor, and modern assisting tools like Large Language Models (LLM) are not utilized to reduce the workload. To address this, we have designed and implemented a modern, semi-automated approach for creating datasets, encompassing tasks such as KBQA, Machine Reading Comprehension (MRC), and Information Retrieval (IR), tailored explicitly for low-resource environments. We executed this pipeline and introduced the PUGG dataset, the first Polish KBQA dataset, and novel datasets for MRC and IR. Additionally, we provide a comprehensive implementation, insightful findings, detailed statistics, and evaluation of baseline models.
Anthology ID:
2024.findings-acl.652
Volume:
Findings of the Association for Computational Linguistics: ACL 2024
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Lun-Wei Ku, Andre Martins, Vivek Srikumar
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
10978–10996
Language:
URL:
https://aclanthology.org/2024.findings-acl.652
DOI:
10.18653/v1/2024.findings-acl.652
Bibkey:
Cite (ACL):
Albert Sawczyn, Katsiaryna Viarenich, Konrad Wojtasik, Aleksandra Domogała, Marcin Oleksy, Maciej Piasecki, and Tomasz Kajdanowicz. 2024. Developing PUGG for Polish: A Modern Approach to KBQA, MRC, and IR Dataset Construction. In Findings of the Association for Computational Linguistics: ACL 2024, pages 10978–10996, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
Developing PUGG for Polish: A Modern Approach to KBQA, MRC, and IR Dataset Construction (Sawczyn et al., Findings 2024)
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PDF:
https://aclanthology.org/2024.findings-acl.652.pdf