CCARF Practice Question

Paper 4 · Question 12

D4 Prompt Engineering & Structured Output · Paper 4

The moderation system uses tool_use with a JSON schema for classification output. All fields including 'sub_category' and 'target_demographic' are marked as required. Auditors discover that when a post is spam (which has no target demographic), the model fabricates plausible-sounding demographics like 'general public' or 'young adults.' What schema change prevents this fabrication?

• A.Add a validation step that rejects any target_demographic value returned for a post that has been classified as spam, before the record is written.
• B.Add a prompt instruction telling the model to leave 'target_demographic' empty whenever a post is spam and the field does not apply.
• C.Remove 'target_demographic' from the schema entirely, on the grounds that its presence is what causes the fabrication in the first place.
• D.Make 'target_demographic' nullable so the model can return null when the field does not apply instead of fabricating a value.

Show answer & explanations

Correct answer: D

A: Post-hoc validation catches the problem but does not prevent it. The model still fabricates values; they are just rejected after the fact. Schema design should prevent fabrication at the source.

B: Prompt instructions cannot override a schema that marks the field as required. The JSON schema enforces the constraint at the API level, and the model must comply with the schema regardless of prompt instructions.

C: Removing the field loses valuable data for categories where target demographic is genuinely relevant (hate speech, harassment). The fix is making it nullable, not removing it.

D: Required fields pressure the model to produce a value even when none exists. Making the field nullable gives the model a legitimate way to indicate 'not applicable,' eliminating the incentive to fabricate. This is the standard pattern for fields that apply conditionally.

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