AI-102 Practice Question: Implement natural language processing solutions
You are deploying a custom question answering solution in Azure AI Language. You need to ensure that the knowledge base can handle synonyms and alternative phrasings for questions. Which THREE strategies should you implement? (Select THREE.)
⚠ Common exam trap
Watch out — candidates often confuse the confidence threshold (a post-ranking filter) with a mechanism for handling synonyms or alternative phrasings, when in fact it only controls the minimum score required to return an answer and does not expand the knowledge base's linguistic coverage.
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
✓
Add alternative question phrases to each QnA pair.
Adding alternative question phrases to each QnA pair directly expands the surface area of possible user queries that will match a given answer. This is a core feature of custom question answering in Azure AI Language, allowing you to predefine synonyms and rephrasings for each QnA pair without relying on external logic.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Add alternative question phrases to each QnA pair.
Why this is correct
Alternative phrases help the model match different phrasings.
- ✗
Use a custom question answering project type instead of the prebuilt one.
Why it's wrong here
Project type does not affect synonym handling.
- ✗
Increase the confidence threshold to 0.9 to reduce false positives.
Why it's wrong here
Increasing threshold reduces matches, does not help with synonyms.
- ✓
Enable active learning to suggest new question variants from user queries.
Why this is correct
Active learning improves the model by suggesting alternative phrasings.
- ✓
Utilize the synonym feature to map equivalent terms.
Why this is correct
Synonyms allow the model to treat different words as equivalent.
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