Ontology Coherence is the structural consistency and stability of an entity's identity, relationships, capabilities, and definitions across machine-readable and human-facing environments.
High Ontology Coherence allows AI systems to interpret an entity reliably and without material ambiguity. Its schema, public language, canonical identity, relationships, and contextual references reinforce the same underlying truth across surfaces and over time.
Ontology Coherence is maintained through Entity Engineering™, Schema Sovereignty™, synchronized updates, stable canonical references, and continued validation across major AI systems and knowledge environments.
Its principal failure state is Cross-Ontology Drift: the progressive divergence of an entity's identity or meaning across websites, schema, APIs, platforms, knowledge graphs, and model interpretation.
When coherence is strong, AI systems can confidently attribute meaning and authority. When drift emerges, the entity may remain visible while its interpretation fragments, weakening Entity Clarity, Crawl Parity, Interpretive Control, and Ontology Authority.
Ontology Coherence is the structural prerequisite for Ontology Authority and the foundation for achieving Default Reference Layer status.
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