What Is a Knowledge Graph? Definition and Example

A knowledge graph is a structured database of entities (people, organisations, places, products) and the relationships between them. Google introduced its Knowledge Graph in 2012 to help Search understand "things, not strings" (Google). Knowledge graphs help systems answer factual questions, disambiguate names and connect a brand to its founders, products and locations.

How is a knowledge graph structured?

Facts are stored as connections between entities:

Illustrative example.

Which knowledge graphs matter for marketers?

• Google's Knowledge Graph, which powers knowledge panels in Search.
• Wikidata, a free, collaborative knowledge base that other projects reuse (Wikidata).
• Proprietary graphs inside AI companies and data providers, which aren't public.

How do you influence what a knowledge graph says?

1. Publish consistent facts on your own site, especially an About page.
2. Add Organization structured data with official profile links (Google).
3. Keep reference profiles accurate where you're eligible, following each site's rules.
4. Earn coverage that states key facts clearly.

There's no direct submission for Google's Knowledge Graph. If you have a knowledge panel, you can claim it and suggest changes.

Why it matters for GEO

AI answers about "who makes X" or "where is Y based" often rely on structured facts. If those facts are wrong or missing, answers may be too. Checking your knowledge panel and Wikidata entry, where one exists, is a quick accuracy audit.

Common mistakes

• Assuming a knowledge panel exists for every brand; many smaller companies don't have one.
• Creating reference entries that don't meet the site's notability or sourcing rules; they're likely to be removed.
• Letting facts drift between your About page, structured data and profiles.

Related

• Entity
• sameAs
• Grounding