Knowledge Graph
A structured map of entities and how they relate.
Technical Term
Full explanation
A knowledge graph is a structured database of entities and the relationships between them, used by search and AI systems to understand how people, brands, and concepts connect.
A knowledge graph stores entities as nodes and their relationships as connections between them: a company node linked to its founder, its industry, its headquarters, and its products. Systems query this structure directly for facts, rather than inferring them fresh from unstructured text each time.
Getting into a knowledge graph, whether Google's or another system's equivalent, generally requires the kind of independent, verifiable evidence that structured sources like Wikipedia and Wikidata are built on. That is a higher bar than publishing content, which is part of why it functions as such a durable signal.
Why this matters
Presence in a knowledge graph is one of the strongest forms of structural authority, because it is where a system stores what it considers settled about an entity.
Example
A company with an entry in a public knowledge graph has its founding date, headquarters, and industry classification available to any system that queries the graph, rather than each system independently inferring those facts from scattered web pages.
Where this sits
Knowledge Graph belongs to Search, SEO & Generative Optimization, one of the seven layers of the Aingworth Glossary. The established disciplines brands use to improve discoverability. Useful, and often necessary, but tactics that sit on top of a brand's underlying authority infrastructure rather than replace it.
Related terms
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