Entity recognition: How ChatGPT perceives your brand
What entity recognition is, why it's crucial for GEO, and how LLMs build an internal picture of your company. No unnecessary theory - just practical implications for marketing.
Try this as an experiment: type your company name into ChatGPT and ask what it knows about it.
If the answer comes back quickly, specific and accurate - congratulations, ChatGPT knows you as an entity. If the answer is vague, hedged or incorrect - you have a GEO problem that matters more than keywords and backlinks.
It's called entity recognition, and it's the foundation of how large language models "think" about companies and brands.
What an entity is in the context of LLMs
In AI terms, an entity is a clearly identifiable object - it can be a company, a person, a product, a place or a concept. An entity has:
- An unambiguous identity - it's clear what or who it is
- Attributes - properties that describe it
- Relationships - how it connects to other entities
Example: "Apple" is an entity. It has attributes (technology company, headquartered in Cupertino, founded by Jobs and Wozniak) and relationships (competes with Google, makes the iPhone, Steve Jobs is linked to Pixar).
LLMs build this "entity graph" automatically from the data they are trained on - billions of web pages, articles, discussions and documents.
How an LLM recognizes your company
Entity recognition by an LLM is the result of a process that, simplified, works like this:
1. Frequency of occurrence: How often does the company name appear in the training data? Companies that are written about more often and in more places are recognized more reliably.
2. Consistency of information: Is the information about the company consistent across different sources? If your website says one thing, LinkedIn another and a media outlet a third, the model builds an inconsistent picture.
3. Contextual association: What concepts, industries and other entities is the company associated with? This determines the contexts in which the model will mention the company.
4. Source quality: Are the sources where the company is mentioned considered authoritative by the model? Citations in respected media carry more weight than mentions on anonymous forums.
Why entity recognition is GEO priority number one
Keyword-based SEO works on the principle: "The customer searches for term X, my page contains it, I show up in the results."
GEO works differently: the AI builds an internal model of the world, and within that model it decides which entities are relevant for a given context.
If your company isn't part of that internal model - or is part of it only as a fuzzy, ill-defined entity - the AI won't spontaneously recommend you. It doesn't matter how well optimized your keywords are.
Example: A customer asks ChatGPT: "What are the best B2B SaaS tools for project management?" The AI traverses its entity graph for the categories "B2B SaaS", "project management", "tools". Companies that are strong entities in these categories make it into the answer. The rest don't.
What strengthens entity recognition
Organization schema markup: Structured data directly on your website tells AI crawlers exactly what your company is. Name, description, founder, area of operation, contact details - all in a format LLMs can process easily.
Consistent information across platforms: LinkedIn, your About page, press releases, media coverage - if you present the same key facts everywhere, the model builds a firmer and more accurate entity.
Expert associations: The founder or a key person as an entity linked to the company. Author bios on articles, a LinkedIn profile, expert contributions - these are the relationships that strengthen entity recognition.
Direct AI context via llms.txt: A file that tells AI crawlers directly how to describe your company. The most direct route to shaping your entity representation.
Citations in other sources: When other authoritative sources write about your company - media, industry blogs, analyses - it strengthens the weight of your entity in the model.
What weakens entity recognition
- A vague or generic company description: "We are an innovative company focused on customer satisfaction" tells the model nothing concrete.
- Inconsistent information: Different names, different service descriptions, different contact details in different places.
- Missing author bylines: Content without an identifiable author is less trustworthy to an LLM.
- An isolated website: The company exists only on its own site with no external mentions anywhere.
How to test your company's entity recognition
A quick three-step test:
- Type your company name into ChatGPT or Gemini and ask what it knows about it
- Check whether the model correctly identifies your industry, what the company does and who runs it
- Ask: "If someone is looking for [your service] in [your location], would you mention this company?"
The results will tell you a lot about your current state of entity recognition. The ideal outcome: an accurate, concise and correctly contextualized answer.
Frequently asked questions
What is entity recognition? A language model's ability to recognize your company as a specific entity — knowing what it does, where it operates and what sets it apart. Without a recognized entity, AI can't recommend you, even if it reads your content.
How do I test whether AI knows me as an entity? Ask ChatGPT, Gemini and Perplexity: "What do you know about [company name]?" and "Would you mention this company if someone is looking for [your service] in [location]?" The ideal is an accurate, concise and correctly contextualized answer.
What strengthens entity recognition the most? Consistent company information across your website and external sources, Organization schema markup, third-party mentions (directories, media, communities) and an llms.txt file with an unambiguous entity identification.
How long does it take to build a recognizable entity? Technical signals (schema, llms.txt, consistency) can be deployed within days. External mentions that confirm the entity take weeks to months to build — which is why entity building is an ongoing discipline, not a one-off task.
Entity recognition is one of the key parameters we analyze as part of a GEO audit. If you don't know how AI systems currently perceive you, we'll be happy to find out for you.
Founder of the first GEO studio in the Czech Republic. He helps companies become an authority for ChatGPT, Gemini and Perplexity.
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