Ontology-Grounded Modeling of Dynamic Processes: A Case Study in Conflict Analysis

By: Bahareh Fatemi, Fazle Rabbi, Andreas Opdahl, Yngve Lamo, Adrian Rutle

Abstract

Dynamic processes such as conflict escalation, disease progression, or policy change often involve entities transitioning through structured states over time. Capturing these evolving trajectories in a way that is both formally rigorous and adaptable to unstructured data remains a challenge. In this paper, we present a hybrid approach that integrates formal modeling techniques with large language models (LLMs) to support structured reasoning over dynamic phenomena. Although LLMs offer powerful capabilities for information extraction, their use as standalone analytic tools in sensitive domains is limited, as they are prone to generating unreliable outputs and lack grounding in domain theories. To address this, we propose a framework that combines LLM-based event extraction with ontology-grounded knowledge graph construction, using constraint-preserving graph transformations to ensure semantic and structural validity. We demonstrate the framework in the conflict domain by constructing an ontology based on Glasl’s conflict escalation model and using it to guide structured event modeling and trajectory analysis. We implement a prototype system demonstrating the framework in the conflict domain, and present experimental results on an event dataset from ACLED.

Keywords

Dynamic Process Modeling, Ontologies, Knowledge Graphs, Graph Transformation, Large Language Models

Cite as:

Bahareh Fatemi, Fazle Rabbi, Andreas Opdahl, Yngve Lamo, Adrian Rutle, “Ontology-Grounded Modeling of Dynamic Processes: A Case Study in Conflict Analysis”, Journal of Object Technology, Volume 25, no. 3 ( 2026), pp. 3:15-28, doi:10.5381/jot.2026.25.3.a2.