1Z0-1127-25 Prompt Engineering Practice Question
An AI application uses chain-of-thought prompting to solve math problems. The team observes that the model sometimes arrives at correct answers but with flawed reasoning. Which technique can specifically help by aggregating multiple reasoning paths?
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
✓
Self-consistency prompting
Self-consistency generates several reasoning chains and selects the most common answer, improving robustness even if some chains have flawed steps.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Role prompting
Why it's wrong here
Role prompting sets the persona but does not address reasoning quality or aggregation.
- ✓
Self-consistency prompting
Why this is correct
Self-consistency samples multiple chain-of-thought outputs and chooses the most consistent answer, effectively filtering flawed reasoning.
- ✗
Tree-of-thought prompting
Why it's wrong here
Tree-of-thought explores branching paths but does not aggregate multiple paths to select the most consistent answer.
- ✗
Few-shot prompting
Why it's wrong here
Few-shot provides examples but does not aggregate multiple reasoning paths.
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