AI-900 Sentiment Analysis Practice Question
A hotel chain wants to analyze thousands of guest reviews to understand the overall tone of feedback (positive or negative) and to extract the most commonly mentioned features (e.g., 'room cleanliness', 'staff friendliness', 'breakfast'). Which two Azure AI Language features should they combine?
⚠ Common exam trap
Test-takers frequently confuse key phrase extraction with entity recognition or entity linking, thinking that extracting features requires named entity recognition, when in fact key phrase extraction is designed to pull out multi-word phrases like 'room cleanliness' that are not necessarily named 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
✓
Sentiment analysis and key phrase extraction
The scenario requires two objectives: understanding the overall tone (positive/negative) and extracting commonly mentioned features. Sentiment analysis directly provides the tone. Key phrase extraction identifies important phrases like 'room cleanliness'. Therefore, the correct combination is sentiment analysis and key phrase extraction (Option A). Option C (key phrase extraction and entity linking) lacks sentiment analysis, so it does not fully address the requirement. Entity linking helps disambiguate entities but does not capture tone, making Option C incomplete.
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 and key phrase extraction
Why this is correct
Correct. Sentiment analysis provides the overall tone, and key phrase extraction identifies commonly mentioned features.
- ✗
Entity recognition and language detection
Why it's wrong here
Incorrect. Entity recognition identifies named entities (people, places), but not overall tone; language detection is unrelated.
- ✗
Key phrase extraction and entity linking
Why it's wrong here
Incorrect. While key phrase extraction extracts features, entity linking does not provide sentiment analysis, which is required to understand tone.
- ✗
Text summarization and sentiment analysis
Why it's wrong here
Incorrect. Text summarization produces a condensed version of the text, but it does not provide sentiment analysis or extract specific features.
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Question Answering with Language Service
Key term
Azure AI Language
Azure AI Language is a cloud-based service from Microsoft that uses natural language processing to understand, analyze, and generate human language for applications.
Key term
Key phrase extraction
Key phrase extraction is an Azure AI service feature that automatically identifies and extracts the most important words and phrases from a piece of text.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-900 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-900 exam.