The Ontology Merging Problem

When learning ontologies from text, every new document can introduce entities that may be semantically identical to existing ones but named differently. Or worse, genuinely conflicting definitions.

This requires sophisticated merging and alignment pipelines that add complexity and can introduce errors. The more documents you process, the more merging decisions you make, the more opportunities for inconsistency.

Database-derived ontologies avoid this entirely: the schema is the single source of truth.

Related: 04-atom—schema-stability-advantage