The article challenges RDF’s focus on global IRIs, showing how conversational and narrative contexts rely on deferred classification, consensus and scoped definitions rather than fixed identifiers. It outlines approaches—contextual definitions, master data management, local IRIs and self-learning AI—to build flexible, locally scoped ontologies.

• Real conversation shows meaning is built incrementally through context, not looked up via fixed global identifiers like RDF's IRIs/URIs
• Understanding of a term (like "bill") solidifies through accumulating clues and social consensus, mirroring how ontologies actually form in practice
• Different organizations naturally build conflicting local schemas for the same concept (e.g. "Customer"), so forcing one universal identifier without first aligning schemas creates clashes
• True interoperability comes from scoped, negotiated consensus between authorities rather than dumping all terms into one master global ontology