Historically, knowledge engineering required specialized taxonomists manually drafting Web Ontology Language (OWL) schemas. Today, self-bootstrapping ontologies leverage Large Language Models to identify candidate entity types, hierarchical parent-child relationships, and directional properties autonomously.
Dynamic Schema Convergence
The recursive pipeline extracts entity-relationship candidates across document batches, groups synonyms using embedding clustering, and prompts reasoning models to resolve schema conflicts. The outcome is an evolving taxonomy that scales alongside enterprise data.