WorldPT: An Ontology-Driven, Directed Multilayer Repository for Computational Narratology, Structural Evaluation and Generative Modeling

The systematic construction of expansive fictional universes, known as worldbuilding, faces significant challenges in maintaining long-range structural consistency, particularly within generative AI architectures prone to “ontological drift”. This paper introduces WorldPT, a novel framework and dataset that formalizes worldbuilding through Directed Multilayer Attributed Graphs. By implementing a Grounding Directionality Axiom and a hexapartite layering system (Structural, Causal, Temporal, Social, Ontological, and Symbolic), we transition from unstructured text-centric models to machine-verifiable narrative structures. The dataset is uniquely curated in Portuguese, aiming to democratize access to advanced computational narratology resources for the Lusophone community. To evaluate the framework, we applied Social Network Analysis (SNA) metrics to a case study of Tolkien’s Middle-Earth universe. Results reveal a “Small-World” topology (average path length of 2.68) and a predominant structural layer (48.7% of connections), quantitatively fingerprinting the setting as a structural-driven worldbuilding. Furthermore, we propose the Cross-Layer Coupling (CLC) metric to identify “lore-shifters” entities whose multidimensionality transcends individual layers. Our findings demonstrate that WorldPT provides a robust foundation for building ontologically stable and interconnected narrative experiences, bridging the gap between graph-based knowledge representation and creative storytelling.