How to Map Entities and Relationships Explicitly

Why it matters

Modern AI retrieval is entity-driven: models build an internal graph of who relates to what. If your site leaves those relationships implicit — an undefined brand, a flat list of pages, no link to established profiles — the model has to infer the structure, and it gets it wrong or assigns low confidence. Explicit relationships ("GEO is part of AI Search Optimisation"; "AI Knowledge Signal publishes the AI Knowledge Signal Framework") let it resolve your graph cleanly.

The strongest move is to connect your entities to ones the model already trusts — Wikidata, LinkedIn, Crunchbase — via sameAs. That anchors your previously-unknown entities to known reference points.

Google’s October 2026 AI Mode and AI Overviews updates added a section surfacing official websites in generated answers (Google — AI Mode and AI Overviews updates (Oct 2026)). That only helps if your official site resolves unambiguously as the canonical entity — confirm your sameAs chain and official-site declarations agree across every property before chasing citation volume.

What good looks like

Your entities and their relationships are defined, consistent, and linked outward:

• A clear hierarchy is mapped: Organisation → Product → Framework → Phases → Subdomains.
• Relationships between concepts are stated explicitly ("GEO → part of AI Search Optimisation → used in LLM systems").
• sameAs properties link your organisation and key entities to Wikidata, LinkedIn, and Crunchbase.
• The hierarchy is consistent across every page, not redefined per page.
• The graph is encoded in schema (Phase 5.1), not only described in prose.

Step by step

1. List your core entities Inventory the entities that matter: your organisation, products, named frameworks, the framework's phases and subdomains, key people, and the concepts you've defined (Phase 2.2 / 3.3).
2. Map the hierarchy and relationships Draw the graph: Organisation → Product → Framework → Phases → Subdomains, plus lateral links ("GEO is part of AI Search Optimisation"). Make the parent-child and "part-of" relationships explicit.
3. Link to established entities with sameAs For your organisation and major entities, add sameAs links to authoritative external records — Wikidata, LinkedIn, Crunchbase. This disambiguates your entity against everything else sharing its name.
4. Keep the graph consistent across pages Use the same entity names and relationships everywhere. A framework that's "the AI Knowledge Signal Framework" on one page and "our method" on another fragments the entity.
5. Encode the relationships in schema Express the graph in JSON-LD using stable @ids and properties like isPartOf, worksFor, brand, and sameAs so the relationships are machine-readable, not just prose (Phase 5.1).

Worked examples

{
  "@context": "https://schema.org",
  "@graph": [
    { "@type": "Organization", "@id": "#org",
      "name": "AI Knowledge Signal",
      "sameAs": [
        "https://www.wikidata.org/wiki/Qxxxxxxx",
        "https://www.linkedin.com/company/your-company",
        "https://www.crunchbase.com/organization/your-company"
      ] },
    { "@type": "CreativeWork", "@id": "#framework",
      "name": "AI Knowledge Signal Publication Framework",
      "publisher": { "@id": "#org" } }
  ]
}

Off-site entity presence audit (2026 update)

Before concluding a Phase 4 audit, search your brand on ChatGPT, Perplexity and Gemini and record which third-party sources are cited alongside you. Then fix what you can, within each platform’s rules:

• Wikipedia: don’t edit an article about your own organisation. Under Wikipedia’s conflict-of-interest guideline, propose corrections on the article’s Talk page with a reliable source and disclose your connection.
• Wikidata: an item needs references to independent sources. A self-created item with no sources is likely to be deleted.
• Forums and reviews: engage openly as yourself; never astroturf. Keep your Google Business Profile and industry listings accurate.
• Google Knowledge Panel: if one exists for your organisation or founder, claim it and suggest corrections through Google’s process.

Common mistakes