Towards Complex Ontology Alignment using Large Language Models

TL;DR

This paper explores how Large Language Models can be used to automate complex ontology alignment tasks, which are traditionally manual and difficult to automate, by leveraging prompt-based methods and rich ontology modules.

Contribution

It introduces a novel prompt-based approach utilizing LLMs and rich ontology modules to advance the automation of complex ontology alignment tasks.

Findings

Demonstrates the potential of LLMs in complex ontology alignment

Proposes a prompt-based method integrating ontology modules

Shows promising results towards automating complex alignments

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.