Quick Answer
The answer is to call Sentiment Analysis, Key Phrase Extraction, and Entity Recognition. These three operations directly map to the required insights because the Azure AI Language service provides dedicated pre-built APIs for each task: Sentiment Analysis scores the overall positive, neutral, or negative tone of the text; Key Phrase Extraction surfaces the main talking points; and Entity Recognition identifies and categorizes specific items like product names, locations, or organizations. On the AI-102 exam, this question tests your ability to match business requirements to the correct Language service features, often appearing as a scenario where you must filter out irrelevant operations like Language Detection or PII Detection. A common trap is confusing Entity Recognition with PII Detection—remember that entities are general categories (e.g., "Contoso Coffee" as a product), while PII is limited to sensitive personal data. For a quick memory tip, think of the acronym SKE: Sentiment, Key phrases, Entities—the three pillars of text insight extraction.
This AI-102 practice question tests your understanding of implement natural language processing solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are using the Azure AI Language service to process customer reviews. You need to extract the following insights: overall sentiment, key phrases, and entity types (such as product names). Which THREE operations should you call?
Key Phrase Extraction
Extracts key phrases.
Language Detection
Why wrong: Detects language, not required.
Sentiment Analysis
Provides overall sentiment.
PII Detection
Why wrong: Detects personal information, not required.
Entity Recognition
Identifies entity types like product names.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Key Phrase Extraction
Options A, B, and C are correct because Sentiment Analysis, Key Phrase Extraction, and Entity Recognition are the operations that provide the required insights. Option D is wrong because Language Detection detects the language, not needed here. Option E is wrong because PII Detection detects personal information, not needed here.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Key Phrase Extraction
Why this is correct
Extracts key phrases.
Related concept
Read the scenario before looking for a memorised answer.
Language Detection
Why it's wrong here
Detects language, not required.
Sentiment Analysis
Why this is correct
Provides overall sentiment.
Related concept
Read the scenario before looking for a memorised answer.
PII Detection
Why it's wrong here
Detects personal information, not required.
Entity Recognition
Why this is correct
Identifies entity types like product names.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Implement natural language processing solutions — This question tests Implement natural language processing solutions — Read the scenario before looking for a memorised answer..
The correct answer is: Key Phrase Extraction — Options A, B, and C are correct because Sentiment Analysis, Key Phrase Extraction, and Entity Recognition are the operations that provide the required insights. Option D is wrong because Language Detection detects the language, not needed here. Option E is wrong because PII Detection detects personal information, not needed here.
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 20, 2026
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.
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