AI-102 Practice Question: Implement natural language processing solutions
You are using Azure AI Language to analyze customer feedback. You need to identify the sentiment of each sentence within a review, not just the overall document sentiment. Which feature should you use?
⚠ Common exam trap
The trap here is assuming that key phrase extraction or custom classification can provide sentiment, when only the sentiment analysis feature with opinion mining returns sentence-level sentiment.
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
✓
Sentiment analysis with opinion mining enabled.
Sentiment analysis in Azure AI Language can return sentiment at the document and sentence level when opinion mining is enabled. This provides the granularity needed to see sentiment per sentence. Key phrase extraction, custom classification, and entity linking do not offer built-in sentence-level sentiment.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Sentiment analysis with opinion mining enabled.
Why this is correct
Sentiment analysis with opinion mining provides sentence-level sentiment and also extracts opinions and aspects. It returns sentiment for each sentence, which directly meets the requirement of identifying sentiment per sentence. Opinion mining adds details about what the sentiment refers to, but the sentence-level sentiment is the key output.
- ✗
Key phrase extraction.
Why it's wrong here
Key phrase extraction identifies main topics or phrases but does not provide sentiment scores or labels. It cannot tell you whether a sentence is positive or negative. While useful for understanding themes, it does not fulfill the requirement to determine sentiment at the sentence level.
- ✗
Custom text classification with sentiment labels.
Why it's wrong here
Custom text classification assigns predefined categories to documents or text, but it does not automatically provide sentence-level sentiment unless you train it with labeled sentiment data. It is not designed for granular sentence sentiment and would require significant effort. The built-in sentiment analysis feature is the correct choice.
- ✗
Entity linking.
Why it's wrong here
Entity linking identifies entities and links them to a knowledge base, such as Wikipedia. It does not analyze sentiment. It is used for disambiguation and enrichment, not for determining positive or negative tone in sentences. Therefore, it does not meet the requirement.
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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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