Why can schema-valid model output still be wrong?

Separates structural validity from factual accuracy, evidence, authorization, and domain invariants.

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TL;DR

A schema validates structure: required fields, types, and allowed shapes. It does not prove that extracted values are factual, that a classification is justified, or that an identifier exists and belongs to the user. The application still validates domain rules and uses evaluation or human review where model judgment matters.

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Practice focus

Whether structured outputs are used as a serialization guarantee rather than mistaken for a truth guarantee.

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Core answer
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Overview
A constrained decoder can ensure that a category field is present and allowed; it cannot prove that the chosen category is supported by the input.
A schema validates structure: required fields, types, and allowed shapes. It does not prove that extracted values are factual, that a classification is justified, or that an identifier exists and belongs to the user. The application still validates domain rules and uses evaluation or human review where model judgment matters.
Checkpoint
Stronger answer
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A model can return a valid orderId string that names the wrong order. It can also choose a valid risk category based on weak evidence. I check identifiers against authoritative systems, validate cross-field rules, require evidence for consequential classifications, and route uncertain cases to a safe fallback instead of accepting the payload merely because it parsed.

Review signals

Use these to catch weak phrasing, shallow reasoning, and risky claims.

Common mistakesCandidateCommon mistakesMistakes that weaken the answer or signal shallow understanding.Open details

Details

Equating constrained decoding with factual correctness.
Trusting model-produced identifiers without lookup.
Using a confidence number as proof of accuracy.
Combining all validation failures into one retry path.

Why can schema-valid model output still be wrong?

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