sameAs schema: anchoring your brand as an entity in the knowledge graph

With the sameAs property in your Organization schema, you tell AI models explicitly which external profiles belong to your brand: your Wikidata item, your LinkedIn page, your registration with the Chamber of Commerce. You tie all those scattered mentions to a single entity, so a model does not have to guess who you are. That is exactly what an AI needs in order to recommend your brand with confidence. Below you will read what sameAs schema does, which sources to put in it and how to implement it concretely in JSON-LD.

What exactly is the sameAs property?

sameAs is a schema.org property that points to a web page which unambiguously confirms your brand’s identity. In the words of schema.org itself, it is “the URL of a reference page that unambiguously indicates the item’s identity”, such as a Wikipedia page, a Wikidata entry or an official profile.

In practical terms, you add sameAs to the Organization object in your structured data. Instead of a single URL, you usually provide a list: your social profiles, your listing in registers and your entity in public knowledge bases. Each URL is a claim that says: “this profile is about the same company as this website.” If you first want to understand how structured data fits into the wider GEO picture, our guide lays the groundwork.

The difference from an ordinary link is important. A hyperlink sends a reader somewhere. sameAs sends a machine a fact about your identity. It is one of the few places where you can tell a model, directly and without noise, who you are.

How does sameAs tell an AI model who you are?

sameAs works because it links your website to an existing node in the knowledge graph instead of treating you as an anonymous domain name. A knowledge graph is the network of entities (companies, people, places) and the relationships between them that search engines and language models use to organise the world.

If your schema points to your Wikidata item, a system can match your domain to that known entity and adopt all the associated knowledge: your sector, your location, your founding year. Google confirms that you may, via sameAs, point to pages with additional information about your organisation, and that you may specify several. Those signals help to disentangle and consolidate your entity.

For AI search, this is crucial. A search engine shows ten links and lets the user choose. An AI system chooses itself and names a handful of brands in a single answer. Whether you are among them depends on how certain the model is about your identity. sameAs reduces that uncertainty by forging scattered mentions into a single coherent profile. This is the same logic at play with grounding, the process by which AI determines what is true: the more reliable sources point to the same entity, the more firmly the model dares to cite.

Which sources do you put in your sameAs list?

Only put sources in your sameAs list that genuinely confirm your entity, not every obscure directory. The value lies in authority and unambiguity, not in numbers. Three types of source carry the most weight.

• Wikidata. This is the strongest sameAs source. Wikidata assigns each entity a unique Q-number (for example Q12345) and feeds directly into the knowledge graph that search engines and models consult. If you do not yet have a Wikidata item, creating one is often the most valuable GEO step you can take. Use the canonical URL of your item as the sameAs target.
• LinkedIn. Your official company page is, for B2B, an authoritative, widely followed profile. It confirms your name, sector and size, and it is heavily consulted when verifying business entities.
• Your business register. In the Netherlands that is your KvK listing (Kamer van Koophandel), in Belgium your enterprise number in the Crossroads Bank for Enterprises (KBO). This is official, legally anchored identity: hard to fake and therefore a strong trust signal.

Supplement with other profiles that are accurate: your YouTube or GitHub channel, industry-specific databases, or a Wikipedia page if you have one. The test stays simple: does this source strengthen your entity, or does it add noise?

How do you implement sameAs concretely in JSON-LD?

You add sameAs as an array inside the Organization object, in a JSON-LD block placed in the <head> of your website. A minimal, correct setup looks like this:

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Customer Impact",
  "url": "https://www.customerimpact.be/",
  "description": "B2B growth partner for SEO, GEO and AI visibility.",
  "sameAs": [
    "https://www.wikidata.org/wiki/Q00000000",
    "https://www.linkedin.com/company/customer-impact/",
    "https://www.kvk.nl/..."
  ]
}

Pay attention to a few things that make the difference between working and useless markup. Use the canonical URL of each source, so the official profile page and not a search result or a shortened link. Keep your name, url and description identical to what appears on the linked profiles. Place the schema preferably on your homepage and, as a site-wide block, on every page. Then validate your markup with a structured data tester so you are sure the syntax is correct.

sameAs is, incidentally, not a standalone trick but part of a wider content architecture for AI extraction. The markup tells the model who you are, the rest of your site has to confirm that story.

Why is sameAs not a guarantee, and what often goes wrong?

sameAs is a strong signal, not a switch that forces your brand into every AI answer. It works together with the rest of your digital footprint and pays off over time, as models and knowledge graphs pick up and confirm your entity.

The most common mistake is inconsistency. If you point to a LinkedIn page where your company name is slightly different from the one on your site, you reinforce the doubt instead of removing it. The same goes for an outdated address in your register or a description that does not match. sameAs is only as reliable as the sources it points to.

A second pitfall is thinking that markup alone is enough. A model also weighs whether there are independent sources talking about you. sameAs confirms your identity, but your authority you build with brand mentions that carry more weight than backlinks. The two reinforce each other: an unambiguous entity makes every mention more valuable.

Honest advice belongs here too. If you have no Wikidata item and a thin online presence, sameAs is not your first priority. You then gain more from building those authoritative profiles themselves. We would rather steer toward visibility that yields qualified leads than a neatly ticked-off schema checklist.

Frequently asked questions about sameAs and the knowledge graph

Do I absolutely need a Wikidata item for sameAs?

No, but it is the strongest source. Without Wikidata you can still link LinkedIn, your business register and other profiles. Creating a Wikidata item is often the most valuable addition, because it feeds directly into the knowledge graph.

How many sameAs URLs may I specify?

As many as genuinely belong to your brand. Google allows several. Choose quality over quantity: four accurate, authoritative profiles are stronger than twelve random directories that add noise.

Does sameAs also work without me ranking in Google?

Yes, because sameAs is about identity, not about rankings. It helps AI systems recognise your entity, including in answers that stand apart from the classic ten blue links. It does not replace good content, but it makes you recognisable.

How quickly do I see the effect of sameAs?

Do not count on an immediate result. Knowledge graphs and models work with update and training cycles, so the certainty builds up over weeks to months. The sooner your markup is correct and consistent, the sooner that process starts.

The short summary

sameAs is the most direct way to tell an AI model who you are. You link your brand, via JSON-LD, to authoritative sources, with Wikidata, LinkedIn and your business register as the core, and you keep the name, URL and description identical everywhere. That way your website becomes a recognisable entity in the knowledge graph instead of an anonymous domain name, and AI dares to cite you with confidence. The technique is simple, but the consistency underneath is what makes the difference.

Do you want to anchor your brand as a watertight entity for AI search? We map your entity, set up your sameAs and structured data correctly and make sure every source tells the same story. Book your free intro call.