1Z0-1127-25 Prompt Engineering Practice Question
A prompt engineer is designing a prompt for legal document analysis. The model should output JSON with a specific structure. Which TWO practices are essential to include in the prompt?
⚠ Common exam trap
Many exam-takers confuse 'stop sequences' (used to truncate output) with 'format constraints' (like JSON schemas), or assume higher token limits and creative temperature settings are universally beneficial, when in fact they degrade reliability for structured data tasks.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Define the JSON schema in the system prompt
Defining the JSON schema in the system prompt explicitly instructs the model on the exact structure and data types required for the output. This is a foundational practice in prompt engineering for structured data generation, as it reduces ambiguity and ensures the model adheres to a predefined format, which is critical for downstream parsing in legal document analysis.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Define the JSON schema in the system prompt
Why this is correct
Defining the schema sets the expected structure.
- ✓
Provide a concrete example of the desired JSON output
Why this is correct
Examples demonstrate the exact format expected.
- ✗
Use a stop sequence of "}"
Why it's wrong here
Stop sequence on closing brace may truncate JSON before it is complete.
- ✗
Increase max tokens to 5000
Why it's wrong here
Max tokens does not directly help with output format adherence.
- ✗
Set temperature to 1.0 for creativity
Why it's wrong here
High temperature reduces reliability; legal tasks need lower temperature.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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