AI-102 Practice Question: Implement natural language processing solutions
You are using Azure AI Language's custom question answering feature. Your knowledge base contains 500 FAQ pairs. Users report that the bot returns irrelevant answers when their questions are phrased differently from the stored FAQs. You want to improve the bot's ability to match paraphrased questions without retraining a full model. Which action should you take?
⚠ Common exam trap
The trap here is assuming that tuning thresholds or enabling chit-chat improves semantic matching, when the real lever is adding alternative question phrasings to the knowledge base.
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 phrasings to each FAQ pair in the knowledge base.
Custom question answering learns from the question-answer pairs and their alternative phrasings. Adding alternative questions provides the model with more surface forms of the same intent, which improves semantic matching for paraphrased user queries without requiring a separate model training process.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable the 'chit-chat' personality in the project settings to make responses more conversational.
Why it's wrong here
Chit-chat adds small-talk responses for casual conversation and does not improve matching of paraphrased FAQ questions. Enabling it would not address the core issue of semantic similarity between user queries and stored questions, and could even dilute relevant answers.
- ✗
Increase the confidence threshold in the project settings to filter low-scoring answers.
Why it's wrong here
Raising the confidence threshold will suppress low-scoring matches, potentially causing the bot to return no answer instead of the correct one. It does not improve the underlying semantic matching, so paraphrased questions would still fail to match relevant FAQs.
- ✓
Add alternative question phrasings to each FAQ pair in the knowledge base.
Why this is correct
Custom question answering uses the alternative questions as additional training data to learn semantic matches. Adding paraphrased variations directly improves the model's ability to match differently worded user queries to the correct FAQ, without requiring a separate retraining pipeline.
- ✗
Switch the project to use a custom text classification model instead of question answering.
Why it's wrong here
Custom text classification assigns categories to text and does not retrieve answers from a knowledge base. Replacing question answering with classification would remove the FAQ retrieval capability entirely, which is not the goal of improving paraphrase matching.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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