Entity & Identity Schema

The schema types that declare who and what is behind a site — Organization, LocalBusiness, and Person — and how they connect that identity to Google's Knowledge Graph.

First published: Jul 1, 2026 · Last updated: Jul 17, 2026 · Advanced
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"Entity & identity schema" is my non-exhaustive label — not an official one — for three schema.org types that declare who or what is behind a site: Organization, LocalBusiness, and Person. Their job isn't rich results; it's disambiguation — telling Google which real-world entity a page belongs to, and connecting that claim to authoritative profiles through sameAs (examples like Wikipedia, Wikidata, verified social accounts — not requirements). LocalBusiness is a subtype of Organization, so use the most specific one that fits; Person is the individual counterpart. This is not a ranking factor and it does not guarantee a Knowledge Panel — sameAs is an identity-resolution signal, not a magic trust lever, and a wrong sameAs value can actively misattribute your entity. Whether it affects AI-answer citation is a plausible but unproven hypothesis, not a documented mechanism. This hub explains the concept and routes you to the three deep dives.

TL;DR — “Entity & identity schema” is my non-exhaustive umbrella term for Organization, LocalBusiness, and Person — the schema.org types whose job is disambiguation, not rich results. They declare which real-world entity a site belongs to and, via sameAs, tie that claim to authoritative records (examples like Wikipedia, Wikidata, verified profiles — not requirements) so engines can resolve it. LocalBusiness is a subtype of Organization — use the most specific type that fits; Person is the individual counterpart. It is not a ranking factor and does not guarantee a Knowledge Panel; sameAs is an identity-resolution signal, not a trust lever, and a reused or misdirected value actively misattributes your entity. Whether it drives AI-answer citation is an unproven hypothesis, not a documented mechanism.

What Google means by “entity”

Entities are identifiable things in information systems; structured data can clarify identity but does not guarantee Knowledge Graph inclusion. Evidence for this claim Official or primary documentation supporting the adjacent article claim, with scope limited to the source's published description. Scope: No ranking guarantee or undisclosed system mechanics are inferred beyond the cited source. Confidence: high · Verified: Schema.org: sameAs Google’s documented structured-data rules remain feature-specific. Evidence for this claim Official or primary documentation supporting the adjacent article claim, with scope limited to the source's published description. Scope: No ranking guarantee or undisclosed system mechanics are inferred beyond the cited source. Confidence: high · Verified: Google: Structured data policies

An entity is a uniquely identifiable real-world thing that Google stores in its Knowledge Graph — people, places, organizations, but also abstract concepts. Google resolves an entity by cross-referencing signals about it across many independent sources: your own website, your social profiles, directories, public databases, notable press mentions, and structured records like Wikidata. Entity schema is your chance to state your identity clearly and point Google at those other records so it can line them up with confidence.

One distinction worth keeping straight: Google’s Knowledge Graph Search API is a developer tool for querying entities — it is not the same system as the ranking-facing Knowledge Panel, and marking up Organization schema doesn’t “submit” you to it. Don’t conflate the API with how identity schema feeds the panel; they’re different things.

Identity schema vs. content schema

This is the central distinction of this hub, so let me draw it cleanly:

  • Content schemaArticle, Product, FAQPage, HowTo, Recipe — describes what is on the page. Its usual payoff is rich-result eligibility: a visible SERP enhancement (stars, price, breadcrumbs).
  • Identity schemaOrganization, LocalBusiness, Person — describes who or what publishes the page. Its payoff is entity understanding and disambiguation, with no visible badge attached.

The practical consequence: identity schema is worth implementing even though it usually produces no rich result. That’s the opposite instinct from most schema work, and it’s why people who only think in “rich results” tend to skip it.

The three identity-bearing types

They aren’t three unrelated siblings — they’re a base type, a specialization of it, and an individual counterpart:

  • Organization is the base/umbrella type for any company or brand. It’s the one almost every site should have.
  • LocalBusiness is technically a subtype of Organization (Thing > Organization > LocalBusiness), for businesses with a physical or local presence — hours, address, service area. Google’s guidance is to use the most specific applicable subtype, so a local business uses LocalBusiness (or a narrower subtype like Restaurant), not generic Organization.
  • Person sits in its own branch (Thing > Person). It establishes an individual identity — an author, a founder or exec, a consultant, a sole proprietor, anyone building a personal brand that needs to be distinguished from same-named people.

A single site often uses more than one: an Organization for the brand and Person markup for the authors, ideally linked into one graph (see @id below).

sameAs and identity resolution

sameAs is the core mechanic. Schema.org defines it plainly: a URL to a reference page that unambiguously identifies the item — Wikipedia, Wikidata, or an official website are the examples schema.org gives, not a required list. Practically, you reference the profiles that genuinely describe you: a Wikidata entry, a Wikipedia page if you have one, verified social accounts. On the Organization side, the homepage is the single most important place to establish brand identity, with at least name, logo, url, and sameAs.

Evidence for this claim Schema.org defines sameAs as a URL to a reference page that unambiguously indicates an item's identity; Wikipedia, Wikidata and an official website are examples, not mandatory destinations. Scope: web Confidence: high · Verified: sameAs

Two rules make or break it:

  1. One value, one entity. A sameAs URL must unambiguously identify the entity — don’t reuse the same sameAs value for two different entities. Reusing or misdirecting it doesn’t just fail to help; it actively misattributes your entity.
  2. sameAs is an identity-resolution signal, nothing more documented than that. It’s schema.org’s mechanism for pointing at another authoritative record of the same entity — not a ranking boost, not a source of “trust,” and not a documented AI-citation lever. Any claim that sameAs does one of those things is a separate, currently unsupported claim; don’t treat it as bundled into the property’s actual job.

A cautionary tale from the industry: Ryan Law at Ahrefs once accidentally set his personal sameAs to Ahrefs’ blog instead of his own author page, which caused Google to misattribute his personal entity to Ahrefs’ site — a small schema slip with a visible, wrong-in-public result. The lesson: entity schema is powerful enough that errors show up in how your brand is represented, so double-check every value. The Ryan Law anecdote is relayed from Ahrefs’ Knowledge Graph guide and is paraphrased here, not quoted verbatim.

@id — connecting your nodes into one graph

@id is a JSON-LD node identifier, full stop — that’s what the JSON-LD spec defines it as: a way to give a node in a graph a stable identifier and reuse that same identifier to refer back to it. Practically, if you have Organization, WebSite, and Person markup scattered across a site, you give the Organization node an @id URI, then point author.@id (on a Person) or publisher.@id (on an Article) at that same URI. That makes “this Article’s author is this Person, who is part of this Organization” unambiguous within the JSON-LD graph you wrote.

What I can’t tell you with the same confidence: how reliably, or in what form, Google’s indexing systems stitch separately-crawled pages into one entity using @id matches. That’s not something Google documents in detail. Treat consistent @id usage as good, spec-compliant practice and a useful implementation convention — not a proven, documented cross-page ranking or entity-linking signal. The deep mechanics of @id belong in the Organization deep dive — for the hub, just know it’s a JSON-LD identifier convention, and be honest that its cross-page effect on Google’s side is an open question, not a documented fact.

Why this matters for AI search / GEO

Here’s the modern stakes, and here’s the honest boundary of what’s proven. Classic ranking and entity recognition are separate problems: you can rank #1 in traditional search and still be invisible to an AI answer engine that doesn’t recognize your brand as a distinct entity — that part is a reasonable inference from how these systems work. What I can’t back with primary evidence is a causal claim that identity schema, sameAs, or @id makes ChatGPT, Perplexity, or AI Overviews recognize or cite you. No AI provider documents that mechanism. So I’ll state it as a hypothesis, not a fact: identity schema is plausible entity infrastructure — accurate, well-linked markup that removes ambiguity a model might otherwise have to guess through — but I don’t have a controlled test showing it changes citation behavior, and you should be skeptical of anyone who claims they do without showing one. This ties into my broader work on AI search / GEO — being ranked and being recognized as an entity look like different battles, but the causal link between “recognized” and “cited” is still an open question, not settled infrastructure.

To be honest about the evidence more broadly: schema is often oversold as an AI-citation lever, and Google’s own reps have been careful here. John Mueller, asked whether lots of schema helps LLMs understand entities, gave the very SEO answer of “yes, no, and it depends” — structured data helps engines understand the entities on a page, but it doesn’t make you rank higher or get labeled “best” in an AI answer; credibility and authority still dominate. The Mueller remark is relayed via Search Engine Roundtable’s coverage and is paraphrased, not presented as a verified verbatim quote.

There’s also a broader disagreement worth surfacing: not everyone thinks “entity SEO” is even a separate discipline. Ahrefs has argued that once Google’s search runs on entities, “entity SEO is just SEO” — ordinary structured data, content quality, and authority-building, not a novel tactic set — and the piece quotes me making the same point: “The entity identification part is more on Google’s end than on our end.” Jump to quote That’s consistent with how I’ve scoped this hub: identity schema is accurate, verifiable markup you control, not a checklist of special “entity optimization” moves — the actual identification and inference work happens on the search engine’s side.

Common mistakes

  • Treating identity schema like any other schema task. It’s not chasing a rich result; it’s disambiguation. Judge it by whether Google can identify your entity, not by whether a badge shows up.
  • Reusing or misdirecting sameAs — the Ryan Law failure mode. One value, one entity; verify every URL points where you mean.
  • Marking up the wrong pages. Google recommends placing Organization schema on your homepage or a dedicated About page — it does not need to be repeated on every page site-wide.
  • Assuming you need Wikipedia. You don’t. Wikidata (much easier to create and edit) plus consistent cross-source signals can establish entity-hood; Wikipedia is one strong signal, not a hard requirement.
  • Expecting a guaranteed Knowledge Panel. Schema can make you eligible; Google decides. There is no “submit for panel” button.

Where to go next

This hub is the map. Each identity type has its own deep dive — implementation, required and recommended properties, and validation:

  • Organization Schema — the base type for any brand or company: where it goes (homepage/About), the name/logo/url/sameAs foundation, and @id graph linking. Start here if you do nothing else.
  • LocalBusiness Schema — the specialized subtype for physical/local presence: address, hours, geo, service area, and choosing the most specific business subtype.
  • Person Schema — establishing an individual’s identity: authors, founders, experts, and personal brands, and how to link a Person to an Organization.

All three sit under the broader structured data / schema markup cluster this hub belongs to — if you’re still fuzzy on the vocabulary, formats (JSON-LD vs. Microdata), and how rich results differ from entity understanding, start with the schema markup overview first, then come back here for the identity layer.

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