AI-103 Implement Generative AI And Agentic Solutions Practice Question
You are evaluating a generative AI application in Azure AI Foundry using automated metrics. You need to measure how well the generated answers are supported by the retrieved source documents. Which evaluation metric should you use?
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
✓
Groundedness
Groundedness measures the extent to which the generated text is derived solely from the provided source context, preventing hallucinations.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Word Error Rate (WER)
Why it's wrong here
WER is used to evaluate speech-to-text transcription accuracy.
- ✓
Groundedness
Why this is correct
Groundedness evaluates whether the model response is faithful to the retrieved context.
- ✗
BLEU score
Why it's wrong here
BLEU score measures n-gram overlap against human reference translations, which is not suitable for semantic RAG evaluation.
- ✗
Perplexity
Why it's wrong here
Perplexity measures how well a probability model predicts a sample, typically used for language modeling quality rather than RAG grounding.
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Last reviewed August 2026 · checked against the official Microsoft exam blueprint
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