Abstract
This paper presents a methodology for building and enriching an ontology from opinionated text, developed in collaboration between industry and academia. The focus of this work is on semantic alignment with Wikidata. Key contributions include a leading category-based scoring and approach and LLM-assisted refinement. Experimental results show that our leading category-based approach significantly improved alignment accuracy, reaching 86.5%. Furthermore, the incorporation of LLM-based refinement further increased accuracy to 90.6%, indicating the potential of this approach for automated ontology enrichment.
Paper Type
Short Paper
DOI
10.62036/ISD.2025.35
Building and Enriching an Ontology on the basis of a Labeled Corpora of Opinions
This paper presents a methodology for building and enriching an ontology from opinionated text, developed in collaboration between industry and academia. The focus of this work is on semantic alignment with Wikidata. Key contributions include a leading category-based scoring and approach and LLM-assisted refinement. Experimental results show that our leading category-based approach significantly improved alignment accuracy, reaching 86.5%. Furthermore, the incorporation of LLM-based refinement further increased accuracy to 90.6%, indicating the potential of this approach for automated ontology enrichment.
Recommended Citation
Waloszek, W. & Pluwak, A. (2025). Building and Enriching an Ontology on the basis of a Labeled Corpora of OpinionsIn I. Luković, S. Bjeladinović, B. Delibašić, D. Barać, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Empowering the Interdisciplinary Role of ISD in Addressing Contemporary Issues in Digital Transformation: How Data Science and Generative AI Contributes to ISD (ISD2025 Proceedings). Belgrade, Serbia: University of Gdańsk, Department of Business Informatics & University of Belgrade, Faculty of Organizational Sciences. ISBN: 978-83-972632-1-5. https://doi.org/10.62036/ISD.2025.35