Google Knowledge Graph Explorer

Free, no signup. Look up an entity by name or machine ID and inspect the labels, descriptions, types, and identifiers returned by Google's Knowledge Graph Search API.

Built by Patrick Stox

Google Knowledge Graph IDs
IDMeaningUse
/m/… Freebase-era machine IDLook up an entity by ID
/g/… Newer Google-native machine IDLook up an entity by ID

Source: Google Knowledge Graph Search API conventions

live Google Knowledge Graph data · top 3 matches

Checks run from our server; we fetch the URL you enter and don't keep the results. Anonymous run-level outcome counters may be used for aggregate research; URLs, domains, IPs, and identifiers are never included, and no statistic is released below 100 runs.

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What will be sent 
 No tool inputs, uploads, pasted source, complete results, query parameters, or URL fragments are attached automatically. You can edit or remove the selected passage above. Browser and anti-abuse metadata is processed for spam prevention. 
  
 
  
 
 
  
 
 
   
    
   

Data from the Google Knowledge Graph Search API. The confidence number is how well an
        entity matched your query — it is not an authority or "entity strength" score, and
        Google is phasing it out. Descriptions come from Wikipedia where shown (licensed
        CC BY-SA). Results are cached for up to 24 hours.

  
 
Sample report
 
Look up Anthropic, and the tool asks the Knowledge Graph API and returns:
 
Illustrative example — a live lookup calls Google's Knowledge Graph API, which this static page can't call; the card shape below matches exactly what the tool renders for a found entity
 
 
 
In the Knowledge Graph
 
Google knows “Anthropic” as an entity.
 
 
 
 
 
Anthropic
 
Technology company
 
Anthropic is an American AI startup company founded in 2021.
Wikipedia →
 
 Organization Corporation Thing 
 
 
 
 KG ID: /g/11h_2zs0j3 see the knowledge panel → match confidence 812 
 
 
 
     
  • The green banner is the headline — it confirms Google's Knowledge Graph has an
            entity matching the query at all, before you look at any detail. See
what "found" vs. "not found" mean ↓.
    •  
  • The mid is the durable identifier — /g/11h_2zs0j3 is the machine ID
            behind this entity's knowledge panel; it's what you'd cite if corroborating the entity elsewhere.
    •  
  • Match confidence isn't a percentage — it's a relative relevance score for how
            well the query matched this entity versus other candidates, useful mainly for comparing results
            within one search, not across different searches.
    •  
 

Below the card, the tool generates copy-paste JSON-LD that reinforces the entity on a page you own:

 
 
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "@id": "https://yoursite.com/#entity",
  "url": "https://yoursite.com",
  "name": "Anthropic",
  "description": "Anthropic is an American AI startup company...",
  "sameAs": [
    "https://en.wikipedia.org/wiki/Anthropic",
    "https://www.google.com/search?kgmid=/g/11h_2zs0j3"
  ]
}
 
 

Paste that inside a <script type="application/ld+json"> tag on the entity's
          home page. The sameAs array links the Wikipedia source and the Google KG ID, so
          your page corroborates the exact entity Google already knows — the same technique covered in
Knowledge Graph SEO.

 
 
 
How to use it
 
     
  1. Type an entity name into the box — a person, company, or brand, e.g.
Anthropic or Patrick Stox. Use the exact name you'd expect
            Google to know it by.
    2.  
  2. Optionally narrow the type filter (Person, Organization, Place,
            Product…) if a name is ambiguous and you want to disambiguate the match.
    3.  
  3. Press Look up. You get a found / not-found verdict and up to the top
            three matching entities.
    4.  
  4. If it's found, scroll to the schema block, add your site URL, and copy
            the generated JSON-LD. If it's not found, work through the playbook.
    5.  
  5. Switch to Compare 2 to look up two entities side by side — useful for
            checking yourself against a competitor. Use Copy share link to send a
            lookup to a colleague.
    6.  
 
 
How to read the result
 
     
  • In the Knowledge Graph (green) — at least one entity matched your query.
            The top match is highlighted; up to three matches are shown in case the
            name is ambiguous.
    •  
  • Not found (red) — nothing matched, so the entity isn't in the Knowledge
            Graph yet. You get the not-found playbook instead of an entity card.
    •  
  • Type chips — the schema.org types Google assigns the entity
            (Organization, Person, Place…). Thing is the catch-all and is dropped from the
            generated JSON-LD unless it's all Google has.
    •  
  • KG ID (mid) — the stable machine identifier, e.g. /m/0d6lp.
            The "see the knowledge panel" link opens google.com/search?kgmid=… for that
            exact entity.
    •  
  • Match confidence — how well the entity matched your query text,
            not an authority or "entity strength" score. It's absent for entities returned by the newer
            API, and Google is phasing it out.
    •  
 
How it works
 

Each lookup calls a small server endpoint (/api/kg-lookup) that queries the
          official Google Knowledge Graph Search API with your name and any type filter.
          The raw response is normalised down to the fields shown — name, mid, types, description, the
          Wikipedia summary, image, and the match score — and cached for up to 24 hours (misses are
          cached too, so repeat "not found" checks are cheap).

 

The JSON-LD is built in your browser from that normalised entity: it picks the
          most specific schema.org type Google reported, keeps the name and description, and assembles a
sameAs array from the Wikipedia URL and the Google KG ID. Add your own site URL and
          it sets url and an @id so you claim the entity's home page as yours.
          Nothing you look up is stored; descriptions shown come from Wikipedia (CC BY-SA).

 
Features
 
     
  • Found / not-found verdict against live Google Knowledge Graph data, top three matches.
    •  
  • Optional entity-type filter (Person, Organization, Corporation, Place, Product, and more)
            to disambiguate common names.
    •  
  • Entity card with description, Wikipedia summary, type chips, image, and the Knowledge Graph
            ID plus a direct link to its knowledge panel.
    •  
  • Copy-paste schema.org JSON-LD generated for the entity, with an optional site URL to claim
url/@id.
    •  
  • A concrete not-found playbook for getting an entity recognised.
    •  
  • Side-by-side comparison of two entities and shareable links for any lookup or comparison.
    •  
 
Limitations
 

This checks Google's Knowledge Graph Search API — not the live knowledge panel, which can differ
          and isn't publicly queryable. A match means Google recognises the entity string, not that a
          knowledge panel renders for it. The free comparison covers two entities at a time. The match
          confidence is a query-relevance number, not authority, so don't read it as entity strength. And
          Google does not publish a guaranteed Knowledge Graph update timeline, so a recent change may not
          appear in this API and this tool cannot predict when it will.

 
Frequently asked questions
 
What is Google's Knowledge Graph?
The Knowledge GraphThe Knowledge Graph is Google's database of entities — people, places, organizations, and things — and the factual relationships between them. It's separate from any single website's structured data: your schema markup is one of many possible inputs to the graph, not the graph itself. is Google's database of real-world entities"Entity & identity schema" is a practitioner label — not an official Google or schema.org category, and not exhaustive of identity-capable schema.org types — for the three main types that declare who or what is behind a site: Organization, LocalBusiness, and Person. — people, companies, brands, places, books, and so on — and the facts and relationships between them. It's what powers the knowledge panel that appears on the right of some search results. When Google recognises your brand or name as an entity, it can attach a machine ID (an mid) to it and understand mentions of you across the web as being about the same thing.
How do I check if my brand is in the Knowledge Graph?
Type the brand or person name into this tool and press Look up. It queries the official Google Knowledge Graph Search API and shows the top matches. If your entity is there you'll see its name, description, types, and Knowledge Graph ID; if nothing matches your name, it isn't in the Knowledge Graph yet and you get a step-by-step playbook for getting in.
What is the match confidence score and is it my entity strength?
No. The confidence number is Google's resultScore — how well an entity matched the text of your query, not how authoritative or well-established the entity is. A common brand name can score high simply because the string matches. Google is phasing this value out of the newer API, and this tool only ever labels it 'match confidence' for that reason. There is no public 'entity strength' score.
What is a Knowledge Graph ID (mid) and where do I use it?
The mid is the stable machine identifier Google assigns an entity, shown in the form /m/0d6lp or /g/11.... It uniquely identifies the entity even if the name is ambiguous. You can view the entity's knowledge panel by searching google.com/search?kgmid=<mid>, and reference it in your schema markupSchema markup is code that uses the schema.org vocabulary to label what your content means so search engines can understand it and show rich results. It's most often written in JSON-LD, and it's not a direct ranking factor. via sameAs so you corroborate which real-world entity your page is about.
My entity isn't in the Knowledge Graph — how do I get in?
Use a consistent, accurate name; publish a clear page about the entity; add appropriate Organization or Person markup; and link to authoritative profiles you control. Google does not publish a guaranteed source list or update timeline for Knowledge Graph inclusion, so treat these as identity-consistency practices rather than an admission checklist.
 
 
     
 Local data 
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Common issues & how to fix them
  
     
  •  Warnings Entity is absent from Knowledge Graph results Fix: Try the entity’s official name and distinguishing context, then document the unmatched state instead of inventing an ID. 
  •  Warnings Multiple Knowledge Graph entities match Fix: Compare type, description, and identifiers, then select only the result that matches the intended real-world entity. 
  •  Warnings Entity type does not match the intended subject Fix: Refine the query with the intended entity type or choose a result whose type matches the subject. 
  •  Information Entity result lacks a useful description Fix: Verify the entity through its type and identifiers, and avoid relying on an absent description for disambiguation. 
    •