OntoKG: Ontology-Oriented Knowledge Graph Construction with Intrinsic-Relational Routing
Yitao Li, Zhanlin Liu, Anuranjan Pandey, Muni Srikanth

TL;DR
This paper introduces OntoKG, an ontology-oriented method for constructing large-scale knowledge graphs with a focus on schema reusability and application versatility, exemplified on Wikidata.
Contribution
It proposes intrinsic-relational routing for schema design, enabling portable, reusable schemas that support diverse ontology-level tasks and are validated through multiple applications.
Findings
Achieved 93.3% category coverage in schema classification.
Constructed a property graph with 34.0M nodes and 61.2M edges.
Validated schema usefulness across five distinct applications.
Abstract
Organizing a large-scale knowledge graph into a typed property graph requires structural decisions -- which entities become nodes, which properties become edges, and what schema governs these choices. Existing approaches embed these decisions in pipeline code or extract relations ad hoc, producing schemas that are tightly coupled to their construction process and difficult to reuse for downstream ontology-level tasks. We present an ontology-oriented approach in which the schema is designed from the outset for ontology analysis, entity disambiguation, domain customization, and LLM-guided extraction -- not merely as a byproduct of graph building. The core mechanism is intrinsic-relational routing, which classifies every property as either intrinsic or relational and routes it to the corresponding schema module. This routing produces a declarative schema that is portable across storage…
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