/terms/knowledge-graph
Knowledge Graph
Citation status
Last checked 2026-05-21
What is a knowledge graph?
A graph database of entities (nodes) and relationships (edges). Each entity has a unique identifier, a type (Person / Organization / Place / DefinedTerm / etc.), and properties (name, description, sameAs links to other databases). AI engines query knowledge graphs to disambiguate user queries — e.g. "what is Python" the language vs. the snake — before generating an answer.
Google's Knowledge Graph (announced 2012) is the most-cited public example. Wikipedia → Wikidata → schema.org entities form the public infrastructure. AI engines build proprietary knowledge graphs by combining this public data with their own crawl and training corpus.
Status in 2026
Foundational and increasingly central. Where 2010s SEO was keyword-based, 2026 SEO is entity-based: ranking depends on whether the engine recognizes your brand, product, or concept as a canonical entity in its knowledge graph. Sites that explicitly mark entities with schema.org (sameAs, identifier, Organization, Person) help AI engines build accurate entity records faster.
Without an entity record, your content is "homeless" — relevant but unanchored, and harder to cite consistently.
How it relates to other concepts
- DefinedTerm schema entries linked to an
inDefinedTermSetform a small knowledge subgraph for terminology — exactly what this site is. - Vector embeddings complement knowledge graphs — graphs encode discrete facts and relationships; embeddings encode semantic similarity. Modern AI engines use both.
- RAG systems often combine knowledge-graph lookup (for entity resolution) with embedding-based retrieval (for content match).
- Together with consistent Organization and Person schema, knowledge-graph signals are the strongest authority inputs into GEO programs.
Related terms
FAQ
- Does the Knowledge Graph affect AI search rankings?
- Yes, indirectly. Entities in the graph carry authority scores that flow into AI answer source selection. Brands without entity records tend to be cited less often even when their content is highly relevant, because the engine has no canonical hook to anchor the citation.
- How do I get my brand into Google's Knowledge Graph?
- Stack consistent entity signals: Organization schema markup, Wikipedia article (where genuinely warranted), Wikidata entry, sameAs links to authoritative profiles (LinkedIn, GitHub, Crunchbase), and recognized industry mentions. No single signal is sufficient; the graph builds confidence from consistent multi-source evidence.
- Is there a Knowledge Graph specifically for AI search?
- Microsoft has the Bing Satori graph. OpenAI and Perplexity have not publicly disclosed knowledge-graph architectures in detail, though behavior suggests they maintain internal entity records built from public sources (Wikipedia, Wikidata) plus crawled content. Coverage differs across engines; a brand can be entity-recognized in one but not another.