{
  "@context": "https://schema.org",
  "@type": "DefinedTerm",
  "schema_version": "1.1",
  "content_item_id": "dictionary-knowledge-graph.en",
  "translation_group_id": "dictionary-knowledge-graph",
  "locale": "en",
  "type": "glossary",
  "section": "dictionary",
  "slug": "knowledge-graph",
  "title": "Knowledge graph",
  "description": "How facts are represented as a network of entities and relationships rather than keywords.",
  "direct_answer": "A knowledge graph is a structure whose nodes represent entities or values and whose edges represent typed relationships. It is a general way to organize knowledge; it is not the same as a Google panel, a JSON-LD file, or a link database, and it does not mean a platform accepted every relationship asserted by a site.",
  "sections": [
    {
      "heading": "Working meaning",
      "paragraphs": [
        "In a simple graph, a GeoAeoAle node may connect to a study through publishes and to a verified profile through sameAs. Edge type matters: placing two names together does not say whether one owns the other, authored it, or was merely mentioned nearby."
      ],
      "source_ids": [
        "google-structured-data",
        "google-ai-search"
      ]
    },
    {
      "heading": "How to distinguish",
      "paragraphs": [
        "A keyword list does not encode relationships, a relational table organizes rows and columns, and a graph treats relationships as first-class objects. A knowledge panel is a product interface; it may draw on a graph, but it is not a synonym for a knowledge graph."
      ],
      "source_ids": [
        "google-structured-data",
        "google-ai-search"
      ]
    },
    {
      "heading": "Example",
      "paragraphs": [
        "The statement “GeoAeoAle publishes article X, written by author Y and based on source Z” can be represented as several nodes and typed edges. If authorship is unverified, that edge should not be added merely to make the graph look complete."
      ]
    },
    {
      "heading": "Testing",
      "paragraphs": [
        "List canonical entities, assign stable identifiers, and verify each relationship against visible text and evidence. Then confirm that JSON-LD does not contradict the page. For an external graph, inspect available APIs or interfaces rather than assuming ingestion."
      ]
    },
    {
      "heading": "Interpretation limit",
      "paragraphs": [
        "A correct local graph helps an editorial team avoid contradictions, but it does not guarantee inclusion in Google's, Bing's, or any AI system's graph. An external system may merge nodes differently, ignore markup, or prefer other sources."
      ]
    }
  ],
  "published_at": "2026-09-11",
  "modified_at": "2026-09-11",
  "data_through": "2026-09-11",
  "next_review_at": "2026-10-11",
  "author": "GeoAeoAle Editorial",
  "origin": "editorial",
  "publisher": "GeoAeoAle Editorial",
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "canonical_url": "https://geoaeoale.com/en/dictionary/knowledge-graph/",
  "claims": [
    {
      "claim_id": "knowledge-graph-scope",
      "text": "Visible content and structured data can state candidate relationships, but only the operator of a knowledge graph can confirm which nodes and edges it stores.",
      "status": "inference",
      "confidence": "medium",
      "source_ids": [
        "google-structured-data",
        "google-ai-search"
      ],
      "publication_status": "public",
      "confidentiality": "public"
    }
  ],
  "sources": [
    {
      "source_id": "google-structured-data",
      "canonical_url": "https://developers.google.com/search/docs/appearance/structured-data/intro-structured-data",
      "title": "Understand how structured data works",
      "publisher": "Google Search Central",
      "source_type": "official",
      "locale": "en",
      "published_at": null,
      "checked_at": "2026-09-11",
      "sha256": "9ec61ebea36695b2e0124aa158fb0192f2716cdc0d8bf47acfd84eb197bdf404",
      "license": "Source terms apply",
      "visibility": "public"
    },
    {
      "source_id": "google-ai-search",
      "canonical_url": "https://developers.google.com/search/docs/appearance/ai-features",
      "title": "Top ways to ensure your content performs well in Google's AI experiences",
      "publisher": "Google Search Central",
      "source_type": "official",
      "locale": "en",
      "published_at": null,
      "checked_at": "2026-09-11",
      "sha256": "c6b267ed42c26ee63151c87d27de45d8882a5b7dc77c3d3dece510b21d63c300",
      "license": "Source terms apply",
      "visibility": "public"
    }
  ],
  "related_slugs": [
    "ai-visibility",
    "retrieval",
    "source-attribution"
  ],
  "limitations": [
    "The term covers implementations with different schemas and identity rules. Name the specific graph and observable interface whenever a conclusion concerns a platform rather than the general data model."
  ],
  "corrections": []
}