AI-102 Practice Question: Implement natural language processing solutions
Which TWO capabilities are provided by Azure AI Language's pre-built entity recognition?
⚠ Common exam trap
Watch out — candidates often confuse the distinct capabilities within Azure AI Language—entity recognition, key phrase extraction, and sentiment analysis—and assume they are all part of the same pre-built entity recognition feature.
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
✓
Identifying names of people
Azure AI Language's pre-built entity recognition includes a category for 'Person' that identifies names of people in text. This is a standard named entity recognition (NER) capability that extracts entities like individuals' names without requiring custom model training.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Identifying domain-specific medical terms
Why it's wrong here
Domain-specific terms require custom NER.
- ✓
Identifying names of people
Why this is correct
Pre-built entity recognition includes Person entities.
- ✗
Extracting key phrases from text
Why it's wrong here
Key phrase extraction is a separate feature.
- ✓
Identifying organization names
Why this is correct
Pre-built entity recognition includes Organization entities.
- ✗
Determining overall sentiment of the text
Why it's wrong here
Sentiment analysis is a separate feature.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-102 exam.