AI-102 Practice Question: Implement natural language processing solutions
You are designing a solution that must extract specific entities from customer emails, such as product names, order numbers, and dates. The solution must be able to learn from a small set of labeled examples and improve over time. Which Azure AI service should you use?
⚠ Common exam trap
Watch out — candidates often confuse pre-built entity extraction (which is out-of-the-box but inflexible) with custom entity extraction (which requires training but adapts to specific needs), leading them to choose Option B because they assume 'pre-built' means 'easier' without recognizing the requirement for custom entities.
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
✓
Custom Entity Extraction
Custom Entity Extraction (D) is correct because it allows you to train a model with a small set of labeled examples to extract domain-specific entities like product names, order numbers, and dates from customer emails. This service supports iterative learning and improvement over time, making it ideal for scenarios where pre-built models lack the required specificity.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
QnA Maker
Why it's wrong here
For question answering, not entity extraction.
- ✗
Pre-built Entity Extraction
Why it's wrong here
Cannot be trained on custom entities; limited to predefined types.
- ✗
Text Analytics for health
Why it's wrong here
Designed for medical entities, not general customer emails.
- ✓
Custom Entity Extraction
Why this is correct
Trainable with small labeled datasets to extract custom entities.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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