{
  "@context": "https://schema.org",
  "@type": "DefinedTerm",
  "schema_version": "1.1",
  "content_item_id": "dictionary-query-fan-out.en",
  "translation_group_id": "dictionary-query-fan-out",
  "locale": "en",
  "type": "glossary",
  "section": "dictionary",
  "slug": "query-fan-out",
  "title": "Query fan-out",
  "description": "Query fan-out is the decomposition of an original question into several related search subqueries whose results are combined for an answer. Subqueries may explore aspects, entities, or time boundaries; their existence cannot be reliably inferred from a long answer or many links alone.",
  "direct_answer": "Query fan-out is the decomposition of an original question into several related search subqueries whose results are combined for an answer. Subqueries may explore aspects, entities, or time boundaries; their existence cannot be reliably inferred from a long answer or many links alone.",
  "sections": [
    {
      "heading": "Working meaning",
      "paragraphs": [
        "Fan-out helps when one query is insufficient for a compound question. A system may separately search product features, current price, limitations, and independent reviews before synthesizing results. The number and wording of subqueries depend on the implementation."
      ],
      "source_ids": [
        "google-ai-search",
        "bing-public-web"
      ]
    },
    {
      "heading": "How to distinguish",
      "paragraphs": [
        "Rewriting replaces one query with another, while fan-out creates multiple branches. Retrieval selects results within each branch, and generation combines the context. A single-query result page and domain diversity alone do not establish fan-out."
      ],
      "source_ids": [
        "google-ai-search",
        "bing-public-web"
      ]
    },
    {
      "heading": "Example",
      "paragraphs": [
        "The question “which laptop should I buy for video editing under $1,500” could create branches for codec performance, memory, display, battery life, and current prices. This illustrates the mechanism; it does not claim that a particular platform always creates those branches."
      ]
    },
    {
      "heading": "Testing",
      "paragraphs": [
        "If a product exposes executed queries, archive them with the original question, time, and results for each branch. If it does not, varying one aspect and analyzing sources can suggest a hypothesis, but it cannot reconstruct the internal trace."
      ]
    },
    {
      "heading": "Interpretation limit",
      "paragraphs": [
        "Fan-out does not guarantee coverage: branches may duplicate one another, omit an important aspect, or inherit bias from the original question. More sources do not prove better verification or that every source influenced the final answer."
      ]
    }
  ],
  "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/query-fan-out/",
  "claims": [
    {
      "claim_id": "query-fan-out-scope",
      "text": "Query fan-out is an internal process unless a platform exposes or documents the subqueries; an external observer sees only outcomes consistent with it.",
      "status": "inference",
      "confidence": "medium",
      "source_ids": [
        "google-ai-search",
        "bing-public-web"
      ],
      "publication_status": "public",
      "confidentiality": "public"
    }
  ],
  "sources": [
    {
      "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"
    },
    {
      "source_id": "bing-public-web",
      "canonical_url": "https://learn.microsoft.com/en-us/microsoft-copilot-studio/guidance/generative-ai-public-websites",
      "title": "Generative answers over public websites",
      "publisher": "Microsoft Learn",
      "source_type": "official",
      "locale": "en",
      "published_at": null,
      "checked_at": "2026-09-11",
      "sha256": "a35496cfe1965d3f1f1862cda5855d6f4825c8316b1ccb5c38722916e94e96d2",
      "license": "Source terms apply",
      "visibility": "public"
    }
  ],
  "related_slugs": [
    "ai-visibility",
    "retrieval",
    "source-attribution"
  ],
  "limitations": [
    "Without exposed subqueries, query fan-out remains an explanatory model for interface behavior. Do not use it to make confident claims about page ranking or the cause of a particular citation."
  ],
  "corrections": []
}