AI-102 Practice Question: Implement natural language processing solutions
You need to analyze customer feedback to determine whether the sentiment is positive, negative, or neutral. Which Azure AI service should you use?
⚠ Common exam trap
Many candidates confuse Key Phrase Extraction or Named Entity Recognition with Sentiment Analysis, because they all involve analyzing text, but only Sentiment Analysis directly outputs positive/negative/neutral labels.
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
✓
Azure AI Language - Sentiment Analysis
Azure AI Language's Sentiment Analysis is the correct service because it is specifically designed to evaluate text and return sentiment labels (positive, negative, neutral) along with confidence scores. This directly matches the requirement to determine whether customer feedback sentiment is positive, negative, or neutral.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure AI Language - Key Phrase Extraction
Why it's wrong here
Key Phrase Extraction returns salient terms from text and assigns no positive, negative or neutral label, so it cannot classify sentiment. It is tempting because it also processes customer feedback text, and would be the correct choice if the requirement were to surface main topics rather than sentiment.
- ✗
Azure AI Language - Named Entity Recognition
Why it's wrong here
Named Entity Recognition extracts people, places, organisations and similar entities, producing no sentiment classification. It is tempting because it also mines customer feedback for structured information, and would be correct if the requirement were to isolate entities such as product or company names.
- ✓
Azure AI Language - Sentiment Analysis
Why this is correct
Azure AI Language Sentiment Analysis returns per-document scores and labels of positive, negative or neutral, directly matching the requirement to classify customer feedback polarity. It is purpose-built for opinion mining rather than translation, OCR or entity extraction.
- ✗
Azure AI Language - Language Detection
Why it's wrong here
Language Detection identifies which language text is written in and returns no sentiment score, so it cannot label feedback positive, negative or neutral. It is tempting because it also analyses raw text, and would be correct if the feedback's language were unknown and needed identifying first.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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