Effectiveness of Security Export Control Ontology for Predicting Answer Type and Regulation Categories
Rafał Rzepka, Akihiko Obayashi · 2024
In this paper we present results of our experiments investigating if an expert knowledge graph can improve Large Language Models accuracy in predicting correct answer labels and regulations related to the topic of security export control. As the lack of related data prevents machine-learning or fine-tuning approaches, we implement prompt expansion by searching most relevant nodes of the graph and adding the expanded context to the prompt. Results of our experiments show that the addition improved answer type selection but clearly hamper the capability of finding a correct regulation category.