Definition #

Definition: An entity graph is a structured representation of named entities and typed relationships. For a brand, the graph can describe the organization, its people, products, category, locations, identifiers, and connections to external sources.

The graph separates entities from the pages that mention them. A page is a document; an entity is the person, organization, product, place, or concept represented in the graph.

Simplified Illustration #

Illustration: A simplified brand graph may be written as the following hypothetical relationship set; it is not observed data.

Organization -> hasFounder -> Person
Organization -> offers -> Product
Organization -> belongsToCategory -> Category
Organization -> identifiedBy -> PublicProfile
Publication -> mentions -> Organization

Brand-Side Graph Elements #

Useful entities and relationships to document include:

  • Organization names, aliases, and canonical website.
  • People and their current roles.
  • Products and the organization that offers them.
  • Parent, subsidiary, and partner relationships.
  • Category labels and service descriptions.
  • Public profile identifiers.
  • Publications that mention or describe the entity.

The record should distinguish a verified fact from an intended category position. A brand's preferred description is not automatically an externally established classification.

Entity Graph and Entity Clarity #

Definition: Entity Graph names the relationship structure.

Definition: Entity Clarity names the coherence of the public identity represented through that structure.

Premise: Within the Machine Relations model, entity-graph work belongs to the Entity Clarity layer and provides a map for finding conflicting names, missing relationships, and ambiguous identifiers.

Working hypothesis (not measured): When public sources express compatible identifiers and relationships, an answer system may be more likely to resolve the intended entity correctly.

Audit Method #

Start with a canonical entity record, then compare it with owned structured data, public profiles, product pages, and earned coverage. Mark conflicts, stale relationships, unsupported category claims, and missing identifiers. Preserve citations for externally asserted facts.

Practical Boundary #

An entity graph is a representation, not proof of visibility or recommendation. Adding a relationship to owned structured data does not establish that an external system accepted it. External behavior requires direct observation under a declared protocol.

Machine Relations definition. This is an established industry term. This page is Machine Relations' definition of it — not a claim to have originated the term.

Machine Relations references

Machine Relations' own methodology, dataset, and research pages related to this term. These are self-references, listed separately from Sources — they are not independent evidence.