AUTOMATED CONSTRUCTION OF AN ONTOLOGICAL MODEL FOR ARMED CONFLICT RESOLUTION STRATEGY USING GENERATIVE ARTIFICIAL INTELLIGENCE

This paper introduces the development and conceptual design of a meta-ontology for armed conflicts - a high-level, formalized framework aimed at capturing the complex and multidimensional nature of modern and historical conflicts. Unlike traditional ontologies that focus narrowly on military or political aspects, the proposed meta-ontology integrates military, political, economic, social, and informational dimensions into a unified model. The research proposes a methodology that combines expert knowledge and artificial intelligence techniques, particularly large language models (LLMs), to assist in the semi-automated generation and refinement of ontological structures. This hybrid approach not only accelerates the ontology construction process but also opens new opportunities for extracting causal mechanisms and strategic patterns embedded in textual sources, including historical analyses, policy documents, and academic discourse. The paper pays particular attention to the applicability of the ontological framework in decision support systems, conflict diagnostics, and strategic foresight. A historical case study - the Franco-Prussian War - is used to demonstrate how the meta-ontology can help to identify key actors, objectives, turning points, and outcomes, offering insights that may be transferable to present-day conflict scenarios. The proposed model lays the foundation for further formalization and implementation of software systems that could aid researchers, analysts, and policymakers. The work is positioned as an initial step toward a broader research agenda, with future papers expected to present more technical details, formal ontological schemas, and empirical validation.