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Ground truth

Referans gerçeklik

D4

Ground truth is task-specific reference information or an accepted target used to compare a system's output.

Review status: 2026-11-26

Technical explanation

It gives an evaluation a reference for comparison, calculation, or judgment.

Conceptual boundaries

Ground truth is not infallible truth; human annotation can contain ambiguity and disagreement.

Provider-neutral example

For a delivery-status task, a reviewed record stating that an order was delivered can be the reference used to compare a model's classification.

Limitations

Ambiguity and disagreement can remain in task-specific reference information and affect how comparison results are interpreted.

Related concepts

Atomic claims and evidence

  1. 1.1NIST AI 600-1, Generative Artificial Intelligence Profile — D4 evidence slice
    Source
    NIST AI 600-1, Generative Artificial Intelligence Profile — D4 evidence slice
    Source role
    Authoritative source
    Exact locator
    MAP 2.3 action text, printed p. 27
    Supported claim
    NIST lists comparison with known ground-truth data as one evaluation method for examining AI-system information integrity.
    Last verification
    Review due
    Scope limitation
    The source presents ground truth as one method among several, not as a universal solution for every evaluation target.
  2. 2.1NIST AI 100-1, Artificial Intelligence Risk Management Framework (AI RMF 1.0) — D4 evidence slice
    Source
    NIST AI 100-1, Artificial Intelligence Risk Management Framework (AI RMF 1.0) — D4 evidence slice
    Source role
    Authoritative source
    Exact locator
    Section 3, printed p. 12
    Supported claim
    NIST says that human judgment should be used when deciding specific metrics and threshold values for AI trustworthiness characteristics.
    Last verification
    Review due
    Scope limitation
    This supports the need to make judgment explicit; it does not prescribe one labelling method or eliminate disagreement.
  3. 3.1Aroyo and Welty, Truth Is a Lie: Crowd Truth and the Seven Myths of Human Annotation
    Source
    Aroyo and Welty, Truth Is a Lie: Crowd Truth and the Seven Myths of Human Annotation
    Source role
    Authoritative source
    Exact locator
    Abstract; "The Seven Myths" and "Disagreement Is Bad," printed pp. 16-17
    Supported claim
    Aroyo and Welty describe human annotation as a process in which ambiguity and disagreement can carry information rather than simply being discarded as error.
    Last verification
    Review due
    Scope limitation
    This is an account of human annotation and does not say that every disagreement is desirable or that every task lacks a usable reference.