Groundedness
Groundedness asks how well the claims in an answer are backed by the sources given to the model. It is one test area, not one worldwide standard score.
Another example
A reviewer checks one answer against three quoted passages. Each claim is marked supported, unsupported, or against the evidence. Even a true claim can be ungrounded if these sources do not support it.
Main parts
- 01answer claims
- 02source context
- 03support judgment
Use it when
Use this term when checking whether an AI answer follows from the evidence it was given.
Do not use it when
Do not use groundedness in place of checking facts, relevance, completeness, or source quality.
Name used in code
claims(answer) ↔ evidence(context) Before you ship
Check the model and prompt versions, source data, versioned evaluation set, and measures. Verify links to evidence, tool permissions, privacy, common failures, decline-to-answer and fallback behavior, human review, monitoring, cost, speed, and rollback.
Outcome: Use or evaluate Groundedness to make AI behavior measurable and tied to evidence. User context: A reviewer checks one answer against three quoted passages. Each claim is marked supported, unsupported, or against the evidence. Even a true claim can be ungrounded if these sources do not support it. AI method or concept: Groundedness. Why it fits: Use this term when checking whether an AI answer follows from the evidence it was given. Do not use it when: Do not use groundedness in place of checking facts, relevance, completeness, or source quality. AI requirements: Define the input and source evidence. Set model and tool permissions. Use versioned evaluation data and measures. Define failure, decline-to-answer, privacy, speed, and cost limits. Operational safeguards: Keep a clear trace and hide sensitive log data. Show users a safe fallback. Mark steps that need human review. Define how to roll back the model or prompt. Acceptance criteria: Record baseline and target measures on a versioned evaluation set. Test edge cases and hostile inputs. Verify fallback, monitoring, permissions, and rollback. Evidence and limits (evidence boundary): No single official standard controls the whole term. Its meaning may change across teams, platforms, or frameworks. Unknowns to confirm: Target task, model and version, evaluation owner, source data, risk limit, tool permissions, and production fallback.
Check this request
Review the current use of Groundedness. Definition: Groundedness asks how well the claims in an answer are backed by the sources given to the model. It is one test area, not one worldwide standard score. Release checks: Check the model and prompt versions, source data, versioned evaluation set, and measures. Verify links to evidence, tool permissions, privacy, common failures, decline-to-answer and fallback behavior, human review, monitoring, cost, speed, and rollback. Before changing code, report the evidence you found, gaps, severity, and the smallest safe fix.