1. Source
A live Knowledge Graph entity lookup. The result identifies where its evidence came from.
Free tool, no account required
Free Knowledge Graph Checker: Entity Matches
The Knowledge Graph Checker is an entity lookup. It sends a brand, person, product or organization name to the public Knowledge Graph and shows the returned matches with their types, descriptions and result scores.
Also known as: KG, entity checker, brand in Knowledge Graph
Evidence shown with sourceNo account requiredNo invented metrics
Run a real check above
Submit a public URL, domain, or keyword. Novaverb will show only the evidence this tool can actually retrieve or measure.
Definition
What is a Knowledge Graph checker?
A Knowledge Graph checker is a tool that looks a name up in the Knowledge Graph, a database of real-world entities and the relationships between them. The Novaverb Knowledge Graph Checker is an entity lookup: the submitted name is sent to the public lookup and whichever entity matches come back are displayed.
Scope
What does the Knowledge Graph checker check?
The Knowledge Graph checker checks whether the public lookup returns an entity for the submitted name. For the top match it shows the entity name, its types, a short description, a longer detail text with a source link, an image when one is returned and the result score. Other possible matches are listed with their own scores.
Who it is for
Who is the Knowledge Graph checker for?
The Knowledge Graph checker is for people who manage how a brand, person, product or organization is identified. A founder of a newer company checks whether the name returns any entity. An SEO checks whether a common brand name resolves to a different, better-known entity. A content lead confirms the returned type and description.
Why it matters
Why use a Knowledge Graph checker?
A Knowledge Graph checker shows how a name resolves before entity work is planned on an assumption. A common name may match another entity entirely, which is what an engine resolving that name would also find. Seeing that early points the effort toward disambiguation: a consistent name, Organization markup and sameAs links.
Method
How does the Knowledge Graph checker work?
The Knowledge Graph checker works as a direct lookup. The submitted entity name is sent to the public Knowledge Graph lookup. Returned names, types, descriptions and result scores are displayed without converting the score into a probability. An empty response is presented as no match returned by this lookup, not proof that the entity is unknown everywhere.
- We query the public Knowledge Graph lookup for the submitted entity name.
- We report returned names, types, descriptions and result scores without converting the score into a probability.
- We present an empty response as no match returned by this lookup, not proof that the entity is unknown everywhere.
Input
What do you enter into the Knowledge Graph checker?
Enter an entity name into the Knowledge Graph checker, not a URL. Use the name exactly as it is published on the site and in its schema.org Organization markup, whether that is the full legal name or the common one. A web address is the wrong input, because the lookup matches names against recognized entities.
Use it like this
NovaverbA brand or organization NAME - we ask the public Knowledge Graph whether it is a recognized entity.Your Company LtdThe full legal or common name works; we match it against recognized entities.Avoid this
https://novaverb.comThis tool takes a name, not a URL - submit the brand or entity name itself.Result
What does the Knowledge Graph checker report contain?
The Knowledge Graph checker report contains a verdict, an entity card and a list. The verdict reads recognized entity or no confident entity match. The card shows the top match with its name, match score, type labels and description. The list holds other possible matches. An evidence boundary states what a match does not measure.
Reading it
How do you read a Knowledge Graph checker result?
Read a Knowledge Graph checker result by reviewing name, type and description together, since a common query can legitimately return a different entity. Confirm that the top match is your entity and not a namesake. Treat the result score as an ordering of relevance for this query, never as a probability or a ranking metric.
Entities explained
Why being a Knowledge Graph entity matters for SEO and AI
The Knowledge Graph is Google's database of real-world entities - brands, people, products, places - and the facts and relationships between them. When your brand is a recognized entity, search engines and AI answer engines can attribute content to you with confidence, which powers knowledge panels, rich results and accurate citations in generative answers.
How entity recognition is built
- Organization schema - declare your entity with schema.org markup, including a stable @id and logo.
- sameAs links - connect your official profiles (Wikipedia, LinkedIn, Crunchbase) so the graph can corroborate you.
- Consistent naming - use one exact brand name everywhere so mentions consolidate to a single entity.
- Authoritative mentions - citations from trusted sources reinforce that the entity is real and notable.
Not matched yet?
Most newer brands aren't in the Knowledge Graph. It's an outcome of the signals above compounding over time - an empty result is a starting point, not a verdict.
Source
Where does the Knowledge Graph checker get its data?
The Knowledge Graph checker gets its data from a live Knowledge Graph entity lookup. The matches, entity fields and result scores are those returned by the public lookup for the submitted query. The tool adds no judgment of its own to the response, and the check does not read your website or its markup.
Limits
What does the Knowledge Graph checker not tell you?
The Knowledge Graph checker does not tell you whether a knowledge panel will appear. The result reports matches returned by the public lookup, and the score ranks relevance for this query only. The score is not a probability or a ranking score, and a match does not measure how prominently the entity appears in search.
Evidence
What does a Knowledge Graph checker result prove?
A Knowledge Graph checker result proves what the public lookup returned for the submitted text: the entity matches with their available types, descriptions and scores. An empty response proves only that this lookup returned no match. Universal non-recognition, a future knowledge panel, a ranking or an AI citation cannot be concluded from either outcome.
2. Boundary
This reports matches returned by the public Knowledge Graph lookup. The score ranks relevance for this query; it is not a probability, a ranking score, or proof that a knowledge panel will appear.
3. Next action
Use the finding to verify a problem, then connect a workspace when you need history, monitoring, or site-wide analysis.
Standards
Which standards does the Knowledge Graph checker apply?
The Knowledge Graph checker applies the published lookup documentation and schema.org. The Knowledge Graph Search documentation defines the returned entity fields and the result score. Schema.org defines the Organization and sameAs markup a site can publish to describe itself. The tool reports the lookup response and does not claim that markup alone creates recognition.
schema.orgOrganization
Organization entity markup
Explains Organization and sameAs markup without claiming that markup creates recognition.
Read the specificationGoogleKnowledge Graph
Knowledge Graph Search
Reports the matches and result scores returned by the public lookup for this query.
Read the specificationWe list a standard only where this tool genuinely reads or measures against it. Where a signal is outside a live check, the result says so instead of implying coverage.
Verification
How can you verify a Knowledge Graph checker result yourself?
Verify a Knowledge Graph checker result by running the lookup again with each published form of the name, the full legal name and the common name, and comparing the entities returned. Then follow the source link beside the detail text of the top match and confirm that the description refers to your organization.
Example
What does a typical Knowledge Graph checker finding look like?
A typical Knowledge Graph checker finding for a newer or niche brand is no confident entity match, which means the entity is not established in this lookup yet. The other case is a brand with a common name: the top match is a different entity with another type label and description, a real and useful result.
Cost
Is the Knowledge Graph checker free?
The Knowledge Graph checker is free and the lookup runs without an account. An account is needed to act on the answer: in a workspace the site itself is connected, so its Organization schema, sameAs links and the signals that reinforce an entity can be audited, and the evidence is saved.
In a workspace
What does a Novaverb workspace add to the Knowledge Graph checker?
A Novaverb workspace adds the site behind the name to the Knowledge Graph checker. GEO & AEO Readiness is the product that continues the job: it inspects captured page structure for answer readiness and tracks provider-observed visibility separately. Evidence is saved, the site is crawled as a whole, and a finding becomes a task that is rechecked.
When to go further
When is a free Knowledge Graph checker not enough?
A free Knowledge Graph checker is not enough when the question is why a name does not resolve, or whether that is changing. One lookup shows one response for one query. Finding inconsistent naming or missing Organization markup takes a crawl of the whole site, and watching recognition build takes measurement repeated over time.
Next step
What should you do after running the Knowledge Graph checker?
After running the Knowledge Graph checker, work through the entity signals in order. Settle on one exact name and use it everywhere. Publish schema.org Organization markup with a stable identifier and logo. Add sameAs links to official profiles. Earn references from reputable sources. Then run the lookup again, since recognition builds as those signals accumulate.
Related tools
Which free tools pair with the Knowledge Graph checker?
The Knowledge Graph checker pairs with free tools that work on the markup an entity lookup cannot see. The Schema Markup Generator builds the Organization JSON-LD that declares an entity. The Meta Tag Checker reads a live page and shows its JSON-LD structured data. The GEO Checker inspects observable page signals that support retrieval, answer extraction and attribution.
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Questions
What do people ask about the Knowledge Graph checker?
The Knowledge Graph checker FAQ answers what an empty result means for a brand, what an entity is and how an organization gets recognized as one. Other questions cover what the result score tells you, how an entity differs from a keyword, why sameAs matters and whether a match means a knowledge panel will appear.
What does the Knowledge Graph Checker check?
It submits the query to the public Knowledge Graph lookup and returns available matches with their entity types, descriptions and result scores.
What does it mean if my brand has no Knowledge Graph match?
An empty result means no confident entity match was found yet, not that your brand can never be recognized or rank. Recognition often grows as consistent references and authoritative signals accumulate over time.
What is an entity in Google's Knowledge Graph?
An entity is a distinct real-world thing, such as a person, company, product or place, that Google understands as a unique node with attributes and relationships, rather than just a matching string of text.
How do I get my organization recognized as an entity?
Publish consistent name, description and details, add schema.org Organization markup with sameAs links to authoritative profiles, and earn references from reputable sources. Consistency across the web helps Google form a confident entity match over time.
What does the result score tell me?
The result score orders how relevant a returned match is to this lookup. It is not a probability, ranking metric or guarantee that a knowledge panel will appear, so verify the entity name, type and description together.
What is the difference between an entity and a keyword?
A keyword is a text string people search. An entity is a disambiguated real-world thing Google understands with attributes and relationships. Entities power richer understanding, letting Google connect concepts beyond literal keyword matching.
Why do entities matter for SEO and AI answers?
Recognized entities help search engines and AI answer engines understand who you are, disambiguate your brand, and surface it in knowledge panels and generative answers, strengthening trust, relevance and visibility beyond keyword matching alone.
How does schema.org Organization markup help entity recognition?
Organization markup declares your name, logo, description and sameAs links to authoritative profiles in a machine-readable form. This structured evidence helps Google connect and confirm your entity, supporting a more confident Knowledge Graph match.
Does a Knowledge Graph match guarantee a knowledge panel?
No. A match confirms Google recognizes the entity, but whether a knowledge panel appears depends on query context, confidence and Google's own display decisions. Recognition is necessary but not sufficient for a panel.
Why is sameAs important for my entity?
sameAs links connect your site's Organization markup to authoritative external profiles that describe the same entity. These corroborating references help Google verify identity and consolidate signals, improving the chance of a confident Knowledge Graph match.