Retrieval and Reasoning

Knowledge Graph

A knowledge graph is a structured database that represents real-world entities (people, companies, products, places) as nodes and the relationships between them as edges, used by search engines and AI systems to reason about who is who and what is connected to what.

Also known as:entity graph, knowledge base graph, KG

Where unstructured text just contains strings, a knowledge graph stores explicit facts: this company is headquartered in this city, this product is made by this brand, this person works at this organization. Each entity has a stable identifier so that two different mentions of the same brand can be recognized as the same thing. Search engines like Google and Bing maintain large knowledge graphs and use them to power knowledge panels and to disambiguate query intent.

AI systems use knowledge graphs (their own or external ones such as Wikidata) to fill in entity-level context when generating an answer. If a model knows that a brand is a company in a specific industry, with specific products and specific competitors, it can answer questions about the brand more reliably and connect it to relevant queries.

Brands influence the knowledge graph mostly by being represented clearly across the open web. Consistent name, address and identifier information, structured data using schema.org Organization and Product types, and accurate entries on platforms like Wikipedia, Wikidata and authoritative industry directories all help the graph link the right facts to the right entity.

Key points

A knowledge graph stores entities as nodes and relationships as edges.
Each entity has a stable identifier so duplicates can be resolved.
Search engines and AI systems use them to reason about entities and context.
Consistent off-site information and structured data improve a brands graph entry.

Frequently asked questions

What is a knowledge graph in SEO?

A knowledge graph is a structured database of entities and the relationships between them. Search engines like Google maintain one and use it to power knowledge panels and to better understand the topic of a query.

How do I improve my brands knowledge graph entry?

Be consistent across the web with your name, contact details and identifiers. Use schema.org Organization and Product markup on your site. Maintain accurate entries in Wikipedia, Wikidata and trusted industry directories.

Related terms

Entity / Entity Authority

An entity is a distinct, identifiable thing in the world (a company, product, person, place or concept), and entity authority is the strength of the signals that connect a brand to its entity record and to the topics it should be associated with in search and AI systems.

Structured Data (Schema.org)

Structured data is machine-readable markup, most commonly in JSON-LD format using the schema.org vocabulary, that labels the meaning of content on a page (Organization, Product, FAQPage, Article, Breadcrumb) so search engines and AI systems can parse it without having to guess from raw HTML.

Semantic Search

Semantic search is a retrieval technique that matches a query to documents by the meaning of the text rather than by exact keywords, usually by converting both the query and the documents into vector embeddings and finding the closest matches.

Brand Visibility (AI)

Brand visibility in AI refers to how often and how prominently a brand appears in answers produced by AI engines such as ChatGPT, Perplexity, Gemini and Google AI Overviews, measured across the queries that matter to the brand.

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