What is a knowledge graph?
A knowledge graph is a database of entities and the facts that connect them, and Google's Knowledge Graph is the best-known one, with millions of entries about people, places and things. A knowledge graph stores things rather than pages: each entity, its facts, and its links to other entities. Search engines use one to tell the company from the unit from the inventor when someone types "Tesla".
What is Google's Knowledge Graph?
It is Google's database of entities. Google describes it as having millions of entries that describe real-world entities like people, places and things, and offers a read-only Knowledge Graph Search API that returns matching entities using standard schema.org types in JSON-LD (Google Knowledge Graph Search API, updated April 26, 2024).
Google also warns that the API is not suitable as a production-critical service, and says it is migrating it to Cloud Enterprise Knowledge Graph. It is a window into the graph, not a way to edit it.
How does a knowledge graph relate to AI answers?
Indirectly, as far as anyone outside can see. A knowledge graph helps a search system decide which entity a query is about, and the results it returns are what an AI engine that searches reads before answering.
No engine publishes how much a given answer leaned on an entity database rather than on retrieved pages and model memory. Treat a clean entity record as reducing ambiguity, not as a ranking lever.
What does a knowledge graph look like in a real example?
"Tesla" resolves to several entities: the company, the SI unit and Nikola Tesla, each with its own facts. In the public Tesla example (Oct 4, 2026), Google AI Overviews answered "What is Tesla?" by opening with the unit before reaching the company.
An entity graph is what lets a system hold those apart. The answer still chose to lead with the unit, which shows that knowing two entities exist is not the same as picking the one the buyer meant.
How does a brand get its facts into knowledge graphs?
Mostly by being described consistently in places these systems read:
- Your website: a plain About page with name, category, founding and location.
- Organization markup with sameAs links to your official profiles.
- Open knowledge bases such as Wikidata, within their notability rules.
- Company and review profiles that match your site word for word.
How does Proofsource check your entity record?
Proofsource audits the profiles engines use to confirm who you are, including Wikidata, Crunchbase, LinkedIn and review sites, and flags any that are missing or disagree with your site; gaps in the entity graph appear in your ranked list of fixes. See Accuracy and identity and Opportunities.
Common questions about Knowledge graph
Can I submit my company to Google's Knowledge Graph?
There is no submission form for the graph itself. Consistent facts on your site and on authoritative profiles are how entities are usually recognized.
Is a knowledge panel the same as the Knowledge Graph?
A knowledge panel is the box Google shows on some searches; the Knowledge Graph is the database behind it.
Do AI chatbots use knowledge graphs?
Some systems combine retrieval with structured data, but the engines do not publish how much any answer relies on one. Measure the answers rather than assume.
Does schema markup put me in the Knowledge Graph?
Not directly. It states facts about your organization in a standard form, which helps systems match your site to the right entity.
Related terms
- Entity
In search and AI, an entity is one distinct, identifiable thing, such as a company, product, person or place, that a system can recognize and keep apart from things with similar names.
- Wikidata
Wikidata is a free, collaborative, multilingual knowledge base that supports Wikipedia and stores facts about entities as structured statements anyone can read and reuse.
- Schema markup (structured data)
Schema markup, or structured data, is code on a page, usually JSON-LD using the schema.org vocabulary, that states facts about the page and its subject in a form machines can read.
- Entity confusion
Entity confusion is when an AI answer about your brand describes, or opens with, a different company or thing that shares or resembles your name.
Worked example: Tesla, public AI answers, Oct 4, 2026: Proofsource's first scan of Tesla, 25 buyer questions and 5 brand questions, one answer per question on each of four engines. A small sample from one brand, shown as an example, not a benchmark.
See where AI leaves you out, and what to fix.
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