External coherence graph
The external coherence graph designates the mapping of public signals (sources, mentions, entities, relations, attributes) that frame how an entity is interpreted by AI systems in the open web. It allows identifying where the narrative is coherent, where it is contradictory, and where it is vulnerable to contamination, collision, or capture.
In interpretive governance, exogenous “truth” is not a single text. It is a graph: relations between sources, entities, and attributes that produce a dominant interpretation.
Definition
External coherence graph is the structured set linking:
- the entity (brand, person, concept, organization);
- external sources (articles, directories, wikis, profiles, citations, aggregators);
- attributes (description, offering, positions, dates, categories, promises);
- relations (belonging, filiation, synonymy, opposition, competition, homonymy).
The graph is called “coherence” graph when it allows measuring signal compatibility among themselves and with the endogenous canon. It reveals zones where AI risks reconstructing an unstable narrative.
