Guide : Entity & Identity Schema

TL;DR — La plupart balisage de données structurées describes what’s on une page (“this is the price,” “this is a review”). Entity & identity schema fait a différent job: it indique moteur de recherches who or ce que is behind le site — a company, a local business, or a person. The three principal types are Organization, LocalBusiness, and Person (pas the seulement identity-capable schema.org types, simplement the three que matter la plupart ici). Leur point is to aider Google identifier vous as a distinct “entity,” pas to earn star ratings. It fait pas directement faire vous rank plus élevé, and it fait pas guarantee vous a Knowledge Panel.

Ce que “entity schema” signifie

Schema.org’s Chose type and sameAs property provide vocabulary pour identifying a chose and linking unambiguous identity références. 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: 2026-07-14 Schema.org: sameAs Google recommends données structurées que accurately represents visible page content and uses stable identifiers consistently. 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: 2026-07-14 Google: Structured data policies

Quand vous lire a web page, vous pouvez tell que “Apple” the company is différent from “apple” the fruit, and que the author “John Smith” is a spécifique réel person and pas simplement a nom. A moteur de recherche has to fonctionner que out from signals. An entity is Google’s word pour a uniquely identifiable real-world chose — a person, a placer, an organization — que it stores in its Knowledge Graph.

La plupart balisage de données structurées étiquettes content: Article, Product, FAQPage. Entity and identity schema is the petit définir of types que étiquettes identity à la place — it declares the chose behind le contenu:

• Organization — pour quelconque company or brand.
• LocalBusiness — pour a business with a réel, physical, local presence (a shop, a restaurant, a dentist).
• Person — pour an individual: an author, a founder, an expert, a personal brand.

“Entity schema” isn’t an official Google or schema.org category, by the façon — it’s simplement a handy nom I utiliser pour ces three identity-bearing types. It’s aussi pas exhaustive: schema.org has autre types que peut identifier a real-world chose (Product, Place, and dozens plus sous the general Thing type). Organization, LocalBusiness, and Person are the three que matter la plupart pour declaring who runs the site, pas the complet liste of identity-capable schema.org types.

Pourquoi c’est important

Marking up votre identity helps Google be certain qui entity votre site is à propos de, au lieu de guessing. Fait bien, que peut feed the Knowledge Graph and prise en charge choses comme a Knowledge Panel or votre logo showing suivant to votre listing. There’s aussi a growing practitioner theory que it plays into si AI outils (ChatGPT, Perplexity, AI Overviews) recognize votre brand as a réel, citable chose — but aucun AI provider documents que connection, so treat it as a plausible hypothesis, pas a lever with proven pull.

But be clair à propos de ce que it fait pas do:

• It is pas a ranking factor. Ajout Organization schema won’t déplacer vous up the results.
• It fait pas guarantee a Knowledge Panel. It peut aider vous become eligible; Google encore decides.

The un property que ties it ensemble: sameAs

The clé ingredient is a property appelé sameAs. It’s how vous tell Google “ce Organization (or Person) is the même entity as ce autre authoritative record” — votre Wikipediune page, votre Wikidata entry, votre verified social profiles. Ceux liens aider Google connecter the dots and confirmer votre identity.

The trap: a sameAs lien pointing at the incorrect profile peut misidentify vous. So it’s a utile signal, pas a magic trust button — and it has to be accurate.

Vouloir the complet version — how entities resolve à travers sources, the Organization vs. LocalBusiness vs. Person decision, @id, and the AI-search angle? Switch to the Avancé tab.

TL;DR — “Entity & identity schema” is my non-exhaustive umbrella term pour Organization, LocalBusiness, and Person — the schema.org types whose job is disambiguation, pas résultats enrichis. Ils declare qui real-world entity a site belongs to and, via sameAs, tie que claim to authoritative records (exemples comme Wikipedia, Wikidata, verified profiles — pas requirements) so engines peut resolve it. LocalBusiness is a subtype of Organization — utiliser the la plupart spécifique type que fits; Person is the individual counterpart. It is pas a ranking factor and fait pas guarantee a Knowledge Panel; sameAs is an identity-resolution signal, pas a trust lever, and a reused or misdirected valeur actively misattributes votre entity. Si it drives AI-answer citation is an unproven hypothesis, pas a documented mechanism.

Ce que Google signifie by “entity”

Entities are identifiable choses in information systems; données structurées peut clarify identity but ne fait pas 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: 2026-07-14 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: 2026-07-14 Google: Structured data policies

An entity is a uniquely identifiable real-world chose que Google stores in its Knowledge Graph — personnes, places, organizations, but aussi abstract concepts. Google resolves an entity by cross-referencing signals à propos de it à travers nombreux independent sources: votre propre website, votre social profiles, directories, public databases, notable press mentions, and structured records comme Wikidata. Entity schema is votre chance to state votre identity clearly and point Google at ceux autre records so it peut line les up with confidence.

Un distinction worth keeping straight: Google’s Knowledge Graph Search API is a developer outil pour querying entities — it is pas the même system as the ranking-facing Knowledge Panel, and marking up Organization schema doesn’t “submit” vous to it. Don’t conflate the API with how identity schema feeds the panel; they’re différent choses.

Identity schema vs. content schema

Ce is the central distinction of ce hub, so let me draw it cleanly:

• Content schema — Article, Product, FAQPage, HowTo, Recipe — describes ce que is on lune page. Its usual payoff is rich-result eligibility: a visible SERP enhancement (stars, price, breadcrumbs).
• Identity schema — Organization, LocalBusiness, Person — describes who or ce que publishes lune page. Its payoff is entity understanding and disambiguation, with aucun visible badge attached.

The practical consequence: identity schema is worth implementing même though it usually produces aucun rich result. That’s the opposite instinct from la plupart schema fonctionner, and it’s pourquoi personnes who seulement think in “rich results” tend to skip it.

The three identity-bearing types

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

• Organization is the base/umbrella type pour quelconque company or brand. It’s the un almost every site devrait have.
• LocalBusiness is technically a subtype of Organization (Thing > Organization > LocalBusiness), pour businesses with a physical or local presence — hours, adresse, service area. Google’s guidance is to utiliser the la plupart spécifique applicable subtype, so a local business uses LocalBusiness (or a narrower subtype comme Restaurant), pas generic Organization.
• Person sits in its propre branch (Thing > Person). It establishes an individual identity — an author, a founder or exec, a consultant, a sole proprietor, anyone building a personal brand que nécessite to be distinguished from same-named personnes.

A unique site souvent uses plus que un: an Organization pour the brand and Person markup pour the authors, ideally lié into un graph (voir @id ci-dessous).

sameAs and identity resolution

sameAs is the core mechanic. Schema.org defines it plainly: une URL to a référence page que unambiguously identifies the item — Wikipedia, Wikidata, or an official website are the exemples schema.org donne, pas a requis liste. Practically, vous référence the profiles que genuinely décrire vous: a Wikidata entry, a Wikipedia page si vous have un, verified social accounts. On the Organization side, the homepage is the unique la plupart important placer to establish brand identity, with at least name, logo, url, and sameAs.

Two rules faire or break it:

1. Un valeur, un entity. A sameAs URL doit unambiguously identifier the entity — don’t reuse the même sameAs valeur pour two différent entities. Reusing or misdirecting it doesn’t simplement échouer to aider; it actively misattributes votre entity.
2. sameAs is an identity-resolution signal, nothing plus documented que que. It’s schema.org’s mechanism pour pointing at un autre authoritative record of the même entity — pas a ranking boost, pas a source of “trust,” and pas a documented AI-citation lever. Quelconque claim que sameAs fait un of ceux choses is a separate, currently unsupported claim; don’t treat it as bundled into the property’s réel job.

A cautionary tale from the industry: Ryan Law at Ahrefs une fois accidentally définir his personal sameAs to Ahrefs’ blog au lieu de his propre author page, qui caused Google to misattribute his personal entity to Ahrefs’ site — a petit schema slip with a visible, wrong-in-public result. The lesson: entity schema is powerful suffisant que errors montrer up in how votre brand is represented, so double-check every valeur. The Ryan Law anecdote is relayed from Ahrefs’ Knowledge Graph guide and is paraphrased ici, pas quoted verbatim.

@id — connecting votre nodes into un graph

@id is a JSON-LD node identifier, complet arrêter — that’s ce que the JSON-LD spec defines it as: a façon to give a node in a graph a stable identifier and reuse que même identifier to refer back to it. Practically, si vous have Organization, WebSite, and Person markup scattered à travers a site, vous give the Organization node an @id URI, alors point author.@id (on a Person) or publisher.@id (on an Article) at que même URI. Que rend “ce Article’s author is ce Person, who is partie of ce Organization” unambiguous dans the JSON-LD graph vous wrote.

Ce que I can’t tell vous with the même confidence: how reliably, or in ce que formulaire, Google’s indexation systems stitch separately-crawled pages into un entity en utilisant @id matches. That’s pas something Google documents in detail. Treat consistent @id usage as bon, spec-compliant pratique and a utile implementation convention — pas a proven, documented cross-page ranking or entity-linking signal. The deep mechanics of @id belong in the Organization deep dive — pour the hub, simplement know it’s a JSON-LD identifier convention, and be honest que its cross-page effect on Google’s side is an ouvrir question, pas a documented fact.

Pourquoi ce matters pour 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: vous pouvez rank #1 in traditional search and encore be invisible to an AI réponse engine que doesn’t recognize votre brand as a distinct entity — que partie is a reasonable inference from how ces systems fonctionner. Ce que I can’t back with principal evidence is a causal claim que identity schema, sameAs, or @id rend ChatGPT, Perplexity, or AI Overviews recognize or cite vous. Aucun AI provider documents que mechanism. So I’ll state it as a hypothesis, pas a fact: identity schema is plausible entity infrastructure — accurate, well-linked markup que removes ambiguity a model pourrait sinon have to guess via — but I don’t have a controlled tester showing it changements citation behavior, and vous devez be skeptical of anyone who claims ils do sans showing un. Ce ties into my broader fonctionner on AI search / GEO — being ranked and being recognized as an entity regarder comme différent battles, but the causal lien entre “recognized” and “cited” is encore an ouvrir question, pas settled infrastructure.

To be honest à propos de the evidence plus broadly: schema is souvent oversold as an AI-citation lever, and Google’s propre reps have been careful ici. John Mueller, asked si lots of schema helps LLMs comprendre entities, gave the very SEO réponse of “yes, no, and it depends” — données structurées helps engines comprendre the entities on une page, but it doesn’t faire vous rank plus élevé or obtenir labeled “best” in an AI réponse; credibility and authority encore dominate. The Mueller remark is relayed via Moteur de recherche Roundtable’s coverage and is paraphrased, pas presented as a verified verbatim quote.

There’s aussi a broader disagreement worth surfacing: pas everyone thinks “entity SEO” is même a separate discipline. Ahrefs has argued que une fois Google’s search runs on entities, “entity SEO is just SEO” — ordinary données structurées, content quality, and authority-building, pas a novel tactic définir — and the piece quotes me making the même 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 ce hub: identity schema is accurate, verifiable markup vous contrôler, pas a checklist of special “entity optimization” moves — the réel identification and inference fonctionner se produit on the moteur de recherche’s side.

Erreurs fréquentes

• Treating identity schema comme quelconque autre schema task. It’s pas chasing a rich result; it’s disambiguation. Judge it by si Google peut identifier votre entity, pas by si a badge montre up.
• Reusing or misdirecting sameAs — the Ryan Law échec mode. Un valeur, un entity; vérifier every URL points où vous mean.
• Marking up the incorrect pages. Google recommends placing Organization schema on votre homepage or a dedicated À propos de page — it fait pas besoin to be repeated on every page site-wide.
• Assuming vous besoin Wikipedia. Vous don’t. Wikidata (beaucoup easier to créer and edit) plus consistent cross-source signals peut establish entity-hood; Wikipedia is un strong signal, pas a hard requirement.
• Expecting a guaranteed Knowledge Panel. Schema peut faire vous eligible; Google decides. Là is aucun “submit for panel” button.

Où to go suivant

Ce hub is the map. Chaque identity type has its propre deep dive — implementation, requis and recommended properties, and validation:

• Organization Schema — the base type pour quelconque brand or company: où it goes (homepage/À propos de), the name/logo/url/sameAs foundation, and @id graph linking. Commencer ici si vous ne faites pashing sinon.
• LocalBusiness Schema — the specialized subtype pour physical/local presence: adresse, hours, geo, service area, and choosing the la plupart spécifique business subtype.
• Person Schema — establishing an individual’s identity: authors, founders, experts, and personal brands, and how to lien a Person to an Organization.

Tout three sit sous the broader données structurées / balisage de données structurées cluster ce hub belongs to — si you’re encore fuzzy on the vocabulary, formats (JSON-LD vs. Microdata), and how résultats enrichis differ from entity understanding, commencer with the balisage de données structurées overview premier, alors come back ici pour the identity couche.

AI summary

A condensed prendre on the Avancé version:

• Ce que c’est: “entity & identity schema” is a practitioner étiquette — non-exhaustive, pas an official category — pour three schema.org types que declare who/ce que is behind a site: Organization, LocalBusiness, Person.
• Identity vs. content schema: content types (Article, Product, FAQPage) décrire lune page and chase résultats enrichis; identity types décrire the publisher and do disambiguation/entity understanding — usually aucun visible badge.
• The three types relate hierarchically: LocalBusiness is a subtype of Organization (utiliser the la plupart spécifique applicable type); Person is the individual counterpart. Sites souvent utiliser several, lié via @id.
• sameAs is the core mechanic: schema.org defines it as une URL to a référence page que unambiguously identifies the entity (Wikipedia, Wikidata, and verified social profiles are exemples, pas requirements). Rules: un valeur = un entity (jamais reuse), and it’s an identity-resolution signal — pas a ranking boost, a trust lever, or a documented AI-citation mechanism. A incorrect sameAs misattributes votre entity (the Ryan Law anecdote).
• @id is a JSON-LD node identifier que lets vous connecter Organization/WebSite/ Person nodes into un graph dans votre markup; how confidently Google stitches que à travers separately-crawled pages isn’t documented, so treat it as a spec-compliant convention, pas a proven cross-page signal.
• Pas a ranking factor; aucun guaranteed Knowledge Panel. It peut faire vous eligible pour panel/logo treatment and feed the Knowledge Graph; Google encore decides.
• AI-search angle: ranking ≠ being recognized as a citable entity, and identity schema is plausible entity infrastructure — but there’s aucun principal evidence it causes AI recognition or citation (Mueller: “yes, no, and it depends”). Ahrefs aussi argues entity SEO isn’t a separate discipline at tout — quoting Patrick: “the entity identification partie is plus on Google’s fin que on our fin.”
• Placement: Organization on the homepage or À propos de page — pas every page.
• Myth-busting: vous don’t besoin Wikipedia (Wikidata + cross-source signals fonctionner).
• Où to go suivant: Organization Schema, LocalBusiness Schema, Person Schema deep dives; commencer with the balisage de données structurées overview si the vocabulary is encore fuzzy.

Documentation officielle

Primary-source documentation on entity and identity types.

Google

• Organization données structurées — the core doc: how Organization schema helps Google comprendre and disambiguate votre organization, the sameAs definition, the “no required properties” guidance, and homepage/À propos de placement.
• Local Business données structurées — the LocalBusiness subtype: adresse, hours, geo, department, and qui business subtypes Google supports.
• Intro to données structurées markup — how Google uses données structurées to comprendre lune page and gather information à propos de the world, and the “most specific applicable type” guidance.
• General données structurées guidelines — quality/spam rules: mark up seulement visible content, utiliser the la plupart spécifique type, garder it accurate.
• Knowledge Graph Search API — the developer API pour querying entities (a outil pour searching the Knowledge Graph — pas the ranking-facing Knowledge Panel system; don’t conflate the two).
• Résultats enrichis Tester / Balisage de données structurées Validator — validate votre markup (the schema.org validator covers types que produce aucun rich result, comme Organization and Person).

Bing / Microsoft

• Bing Webmaster Guidelines — Bing’s prise en charge pour schema.org données structurées.
• Marking up votre site with données structurées — Bing’s structured-data aider and Markup Validator.

Quotes from the source

On-the-record statements. Où une page exposes the text, the lien is a deep lien que jumps to the quoted passage.

Google docs — Organization schema and disambiguation

• “Adding organization structured data to your home page can help Google better understand your organization’s administrative details and disambiguate your organization in search results.” Jump to quote
• On disambiguation properties: “Some properties are used behind the scenes to disambiguate your organization from other organizations.” Jump to quote
• On requis properties: “There are no required properties; instead, we recommend adding as many properties that are relevant to your organization.” Jump to quote
• On sameAs: “The URL of a page on another website with additional information about your organization” — Par exemple, a profile page on a social media or examiner site. Jump to quote

Google — sameAs identity semantics (paraphrase)

• À travers Google’s structured-data docs the consistent instruction is que a sameAs valeur doit unambiguously identifier the entity — vous devezn’t utiliser the même sameAs valeur pour two différent entities. Ce is the mechanic behind entity resolution. Paraphrased: ce phrasing recurs à travers several Google structured-datune pages plutôt que un canonical quotable page, so it’s summarized ici, pas presented as a unique verbatim citation.

John Mueller, Google — schema and LLM/entity understanding (paraphrase)

• Asked si extensive balisage de données structurées helps LLMs comprendre entities meilleur, Mueller reportedly answered que it’s a “yes, no, and it depends” question: données structurées helps engines comprendre the entities on une page and is la plupart valuable pour precise details, but it doesn’t faire an entity rank plus élevé or obtenir labeled “best” in AI réponses — broader authority signals encore dominate. Relayed via Moteur de recherche Roundtable’s coverage; paraphrased, pas confirmed as a verbatim quote. Ne faites pas treat the exact wording as final.

Patrick Stox, quoted by Ahrefs — is entity SEO a separate discipline?

• “The entity identification part is more on Google’s end than on our end.” Jump to quote — from Ahrefs’ “Entity SEO is Just SEO” piece, arguing que la plupart “entity SEO” tactics are ordinary SEO plutôt que a distinct discipline.

Quand to utiliser Organization vs. LocalBusiness vs. Person

Decision shortcuts

• Have a brand/site? → Organization (almost toujours).
• Physical or local business? → LocalBusiness (the spécifique subtype) au lieu de generic Organization — utiliser the la plupart spécifique applicable subtype.
• Named individual to establish? → Person, usually alongside Organization, lié with @id.

Fast facts

• “Entity/identity schema” = pas an official category; it’s a étiquette pour ces three identity-bearing types.
• Core mechanic = sameAs → Wikipedia / Wikidata / verified social profiles.
• Un sameAs valeur = un entity. Jamais reuse or misdirect it.
• Pas a ranking factor. Aucun guaranteed Knowledge Panel.
• sameAs = identity-resolution signal, pas a trust/authority lever.
• Placer Organization on the homepage/À propos de, pas every page.
• Aucun Wikipedia requis — Wikidata + cross-source signals peut establish entity-hood.

Treating identity schema comme a rich-result task

I voir personnes implement Organization or Person markup and alors vérifier the Rich Results Tester, waiting pour a badge que was jamais coming. Pourquoi it’s incorrect: identity schema’s job is disambiguation, pas SERP decoration — la plupart of it produces aucun visible enhancement at tout, so judging it by “did a rich result show up” rend vous conclude the markup “didn’t work” quand it’s en réalité doing exactly ce que it’s supposed to do. Do à la place: judge identity schema by si Google peut confidently identifier votre entity — validate the markup, confirmer sameAs valeurs resolve to the correct profiles, and arrêter expecting a visual payoff.

Reusing or misdirecting a sameAs valeur

The échec mode ici is concrete, pas hypothetical: Ryan Law at Ahrefs une fois had his personal sameAs pointing at Ahrefs’ blog au lieu de his propre author page, and Google misattributed his personal entity to Ahrefs’ site. Pourquoi it’s incorrect: a sameAs URL has to unambiguously identifier un entity — reusing the même valeur à travers two différent entities, or pointing it at the incorrect profile, doesn’t simplement échouer to aider, it actively misattributes who vous are. Do à la place: appliquer the one-value-one-entity rule strictly, and double-check every sameAs URL en réalité points at votre profile avant publishing, pas a lookalike or a parent brand’s.

Marking up Organization on every page site-wide

Some sites repeat complet Organization JSON-LD on every template, treating it comme a tracking pixel. Pourquoi it’s incorrect: Google’s guidance is to placer Organization schema on the homepage or a dedicated À propos de page — repeating it everywhere adds maintenance risk (un stale copy drifts from the rest) sans ajout quelconque signal strength. Do à la place: mark up Organization une fois, on the homepage or À propos de page, and lien autre identity nodes (Person, WebSite) into que un graph via @id plutôt que duplicating the whole block.

Assuming vous besoin a Wikipediune page to be a recognized entity

I regularly hear “we can’t do entity schema, we don’t have a Wikipedia page” as si that’s a blocker. Pourquoi it’s incorrect: Wikipedia is un strong signal among nombreux, pas a requirement — plenty of réel, well-established entities have aucun Wikipediune page and encore resolve fine. Do à la place: créer or claim a Wikidata entry (beaucoup easier to créer and edit que Wikipedia) and garder votre cross-source signals — social profiles, directories, consistent nom/logo usage — consistent; que combination peut establish entity-hood on its propre.

Expecting a Knowledge Panel as a guaranteed outcome

I’ve had personnes demander pourquoi leur nouveau Organization markup didn’t “trigger” a Knowledge Panel dans a week. Pourquoi it’s incorrect: entity schema n’est pas a ranking factor and ne fait pas guarantee a Knowledge Panel — it peut faire vous eligible, but Google decides si and quand a panel apparaît, and there’s aucun “submit for panel” button to press. Do à la place: treat correct, accurate markup as necessary infrastructure, pas a requête formulaire — implement it bien, garder votre sameAs and cross-source signals consistent, and let entity recognition construire over temps plutôt que measuring success contre a panel appearing on schedule.

Vérifier ce que entities votre page en réalité surfaces

My Entity Coverage Analyzer extracts the probable entities on une page, lets vous reconcile qui matches are correct, and drafts transparent about/mentions JSON-LD from le résultat. Run it avant vous écrire quelconque Organization or Person markup by hand — it montre vous ce que a machine déjà infers à propos de lune page’s entities, so votre schema reinforces que reading au lieu de contradicting it.

Confirmer si Google’s Knowledge Graph déjà knows vous

My Google Knowledge Graph Explorer semble up si Google’s Knowledge Graph has resolved a person, company, or brand — returning the entity’s nom, types, description, and machine ID si it exists, plus copy-paste schema.org JSON-LD si it fait and a step-by-step playbook si it doesn’t. Ce is the direct façon to vérifier si votre Organization or Person schema and sameAs liens have en réalité helped Google line vous up as a distinct entity, plutôt que guessing.

Validate votre Organization, LocalBusiness, or Person JSON-LD

My Balisage de données structurées Validator checks JSON-LD or a complet HTML page pour schema.org vocabulary errors, Google’s structured-data requirements, and cross-block @id graph consistency, alors hands back a corrected, copy-pasteable block. Since Organization, LocalBusiness, and Person produce aucun rich result to visually sanity-check, running the markup via a validator is the seulement reliable façon to catch a typo’d property or a broken @id lien avant it ships.

Testez vos connaissances: Entity & Identity Schema

Five rapide questions on Organization, LocalBusiness, Person, and ce que identity schema fait (and doesn’t) do. Pick an réponse pour chaque, alors vérifier.

Ressources utiles

Connexe schema writing

• Balisage de données structurées — the vocabulary overview: schema.org, formats (JSON-LD vs. Microdata/RDFa), résultats enrichis vs. entity understanding. Commencer ici si the basics are fuzzy.
• Balisage de données structurées pour AI — the AI-search angle: pourquoi schema is entity infrastructure, pas a direct citation lever.
• AI Search / GEO — being ranked vs. being recognized as a citable entity by AI réponse engines.

From the industry

• Google’s Knowledge Graph Explained: How It Influences SEO & AI Search (Ahrefs — Despina Gavoyannis & Michal Pecánek, reviewed by Ryan Law) — ce que an entity is, how Google resolves it à travers sources, sameAs pratique, and the Ryan Law sameAs cautionary tale.
• Ce que is the Google Knowledge Graph? (Ahrefs SEO glossary) — a short definition of the entity store ces schema types feed.
• Quand and Comment utiliser knowledge graphs and entities pour le SEO (Moteur de recherche Land) — industry framing on entities and the Knowledge Graph.
• En utilisant @id in Schema.org Markup pour le SEO, LLMs, & Knowledge Graphs (Momentic) — how @id connects Organization/Person/WebSite nodes into un graph.
• Arrêter Overcomplicating Choses. Entity SEO Is Simplement SEO (Ahrefs — Si Quan Ong, quoting Patrick) — the counter-argument que entity SEO isn’t a separate discipline, since identification se produit on the moteur de recherche’s side.

Straight from the source

• Organization données structurées (Google) — the principal implementation doc pour the base identity type.
• schema.org — Organization / LocalBusiness / Person — the vocabulary definitions and complet property listes pour chaque type.
• JSON-LD 1,1 — Node Identifiers (W3C) — the spec definition of @id as a JSON-LD node identifier, independent of quelconque moteur de recherche’s cross-page behavior.

Journal des modifications