Towards Complex Ontology Alignment using Large Language Models

• URL: http://arxiv.org/abs/2404.10329v2
• Date: Mon, 22 Jul 2024 20:07:33 GMT
• Title: Towards Complex Ontology Alignment using Large Language Models
• Authors: Reihaneh Amini, Sanaz Saki Norouzi, Pascal Hitzler, Reza Amini,
• Abstract summary: Ontology alignment is a critical process in Web for detecting relationships between different labels and content. Recent advancements in Large Language Models (LLMs) presents new opportunities for enhancing engineering practices. This paper investigates the application of LLM technologies to tackle the complex alignment challenge.
• Score: 1.3218260503808055
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Ontology alignment, a critical process in the Semantic Web for detecting relationships between different ontologies, has traditionally focused on identifying so-called "simple" 1-to-1 relationships through class labels and properties comparison. The more practically useful exploration of more complex alignments remains a hard problem to automate, and as such is largely underexplored, i.e. in application practice it is usually done manually by ontology and domain experts. Recently, the surge in Natural Language Processing (NLP) capabilities, driven by advancements in Large Language Models (LLMs), presents new opportunities for enhancing ontology engineering practices, including ontology alignment tasks. This paper investigates the application of LLM technologies to tackle the complex ontology alignment challenge. Leveraging a prompt-based approach and integrating rich ontology content so-called modules our work constitutes a significant advance towards automating the complex alignment task.

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