What is an entity for an LLM?
In information systems and natural language processing terminology, an entity is a real or conceptual object to which properties and relationships can be attributed: a person, an organisation, a place, a product, a concept. LLMs do not directly manipulate formal entities (as a database system would), but their training on billions of tokens gives them an internal representation of entities - a kind of "tacit knowledge".
For search engines and LLMs, a well-defined entity is one that is:
- Named consistently (same denomination across all sources)
- Endowed with stable properties (sector, founders, creation date, location...)
- Distinguished from other homonymous entities (disambiguation)
- Connected to other entities via semantically clear relationships
Disambiguation is the process of ensuring that a proper noun - your brand, for example - is clearly associated with a unique entity in engine representations. Without disambiguation, a brand name can be confused with any other concept or entity carrying a similar name in the corpus.
Why this is critical for LLM visibility
When a user asks ChatGPT or Perplexity "what are the best customer service automation tools for e-commerce?", the LLM will scan its representations to find entities matching that description. If your brand is poorly disambiguated - if the sources mentioning it use inconsistent names, contradictory descriptions, or associate it with irrelevant domains - it will be under-represented in the response, or absent.
LLMs function like retrieval systems on their internal representation of the world. The cleaner your entity is in that representation, the better its chances of being selected when the context is relevant.
The seven operational actions
Action 1 - Define and document your core entity
Before any technical action, precisely define what your entity is: official name, category (Organisation? Product? Person?), one-sentence description, precise activity domain, founding date, location, key associated people. This definition must be stable over time and consistent across all your surfaces.
Example of a well-defined entity:
Acme Corp is a French company founded in 2019, publishing a SaaS software for e-commerce customer service automation by artificial intelligence, based in Paris.
This sentence should appear almost word for word on your About page, your company LinkedIn profile, your Crunchbase page, your Wikidata entry if you have one, and in press releases.
Action 2 - Schema.org Organization on all your pages
The schema.org Organization (or Corporation, LocalBusiness as appropriate) is the formal declaration of your entity that engines read directly. It should appear in the <head> or as JSON-LD on your homepage at minimum, ideally on all pages.
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "Acme Corp",
"url": "https://acmecorp.com",
"description": "SaaS software for e-commerce customer service automation by AI",
"foundingDate": "2019",
"foundingLocation": {
"@type": "Place",
"name": "Paris, France"
},
"sameAs": [
"https://www.linkedin.com/company/acme-corp",
"https://www.crunchbase.com/organization/acme-corp",
"https://www.wikidata.org/wiki/QXXXXXXX"
]
}
The sameAs property is particularly important: it links your entity to its representations on other authoritative platforms (LinkedIn, Crunchbase, Wikidata), which helps LLMs consolidate these representations into a single coherent entity.
Action 3 - Name consistency across all channels
Your brand name must appear identically everywhere: website, social media profiles, press mentions, Google Business profiles, sector directories. Any variation fragments the entity representation in LLMs.
Also check descriptions: the formulation of your activity must be consistent between your site, your LinkedIn profile, your Twitter/X bio, your Crunchbase page and the press mentions you control.
Action 4 - Create or enrich your Wikidata entry
Wikidata is the structured knowledge base of the Wikimedia Foundation. It is one of the most important sources for LLMs, which use it as an entity reference during training. A well-completed Wikidata entry for your organisation is a strong entity signal.
For companies that have not yet reached the notability required for Wikipedia (encyclopaedic notability), Wikidata is more accessible - it does not require editorial notability, only verifiable sources. You can create your entry yourself with basic factual information.
Action 5 - Obtain contextual mentions in authoritative sources
LLMs give more weight to entities that appear in sources they consider authoritative: national press, recognised sector publications, academic studies, institutional reports. A mention in The Guardian, TechCrunch, or a Gartner report carries much more weight than a mention on an obscure blog.
PR strategy is not just good for classical SEO (backlinks) - it directly builds the representation of your entity in LLM training corpora.
Action 6 - Cross-channel consistency of entity attributes
Your entity attributes (sector, size, location, products, leadership team) must be consistent across all your digital presences. Inconsistencies create "noise" in the LLM representation of your entity - for example, if your site says you are based in London but your Crunchbase profile says Manchester, the LLM will be uncertain about the location attribute.
Action 7 - Structured About page with biographical data
A complete and well-structured About page is one of the most impactful E-E-A-T actions for disambiguation. It should include: company history, founders with their LinkedIn profiles, precise mission, area of expertise, key figures (clients, countries, industries), press references, partnerships. This page is often the primary source LLMs use to characterise your entity.
How to measure disambiguation
There is no publicly available direct "entity clarity" score. Useful proxies:
- Google Knowledge Panel: if your organisation has a Knowledge Panel in Google SERPs, that is a strong signal that Google has consolidated your entity. Claim and enrich it.
- Direct LLM test: ask ChatGPT, Perplexity and Gemini "What is [your brand]?" and check whether the responses are correct, complete and consistent with each other.
- Contextual citation test: ask "What are the main players in [your sector]?" and check whether you appear.
Perform these tests regularly (every two months) to detect changes following your Entity SEO actions or following events (acquisition, pivot, reputation crisis).
Entity SEO as a long-term investment
Entity disambiguation is a foundational effort that produces effects over 6 to 18 months. LLMs are periodically updated (new training cycles), and changes in your entity representation propagate gradually. Consistency matters more than the intensity of one-off actions.
However, for real-time citations (Perplexity, ChatGPT Search), the effects of content and structure improvements are much faster - a few days to a few weeks after the crawl.