The rapid development and deployment of Large-Language Models (LLMs) has led to growing interest in leveraging ontologies and knowledge graphs to enhance LLM capabilities and address limitations. Combining the semantically rich architectures provided by ontologies and knowledge graphs with the generative strengths of LLMs promises to provide a path towards more explainable artificial intelligence systems, more trustworthy output, and a deeper understanding of vulnerabilities arising from integrated architectures.

On July 15th I will be hosting a Workshop on the Convergence of Large Language Models and Ontologies, as part of the 2024 Formal Ontology in Information Systems conference in Enschede, Netherlands. This workshop, associated with a special issue of Applied Ontology, is dedicated to exploring the convergence of knowledge representation and LLM strategies, design patterns, models, and benchmarks. We aim to bring together researchers, practitioners, and enthusiasts from industry, academia, and government in the interest of exploring possible convergence points and advancing each field.

More information as the program develops can be found here.