- A
Sentiment analysis
Why wrong: Sentiment analysis does not identify language or key phrases.
- B
Summarization
Why wrong: Summarization produces a summary, not key phrases.
- C
Language detection
Language detection identifies the language of the text.
- D
Entity recognition
Why wrong: Entity recognition identifies entities, not key phrases.
- E
Key phrase extraction
Key phrase extraction extracts key phrases from the text.
Question 979 of 993
Identify Language and Extract Key Phrases from Social Media Comments
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 Azure AI Language to analyze social media comments. You need to identify the language of each comment and then extract key phrases. Which TWO features should you use? (Select TWO.)
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
✓
Language detection
Language detection is the correct feature because it identifies the language of each comment, which is a prerequisite for further analysis. Key phrase extraction is the second correct feature because it extracts important terms from the text, directly addressing the requirement to 'extract key phrases' after language identification.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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
Why it's wrong here
Sentiment analysis does not identify language or key phrases.
- ✗
Summarization
Why it's wrong here
Summarization produces a summary, not key phrases.
- ✓
Language detection
Why this is correct
Language detection identifies the language of the text.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Entity recognition
Why it's wrong here
Entity recognition identifies entities, not key phrases.
- ✓
Key phrase extraction
Why this is correct
Key phrase extraction extracts key phrases from the text.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Microsoft Azure AI Language often tests the distinction between features that analyze content (sentiment, entities, key phrases) versus those that identify metadata (language), and the trap here is that candidates might confuse 'key phrase extraction' with 'entity recognition' because both extract terms, but key phrases are broader and not limited to named entities.
Trap categories for this question
Keyword trap
Sentiment analysis does not identify language or key phrases.
Detailed technical explanation
How to think about this question
Language detection in Azure AI Language uses a multilingual model that can detect over 120 languages, returning a language name and a confidence score (0-1). Key phrase extraction leverages a statistical model to identify non-trivial terms, often using TF-IDF or similar algorithms, and is language-aware, meaning it performs best when the input language is correctly identified first. In a real-world scenario, processing multilingual social media comments requires language detection to route text to the correct language-specific key phrase extraction pipeline.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
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
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FAQ
Questions learners often ask
What does this AI-102 question test?
Implement natural language processing solutions — This question tests Implement natural language processing solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Language detection — Language detection is the correct feature because it identifies the language of each comment, which is a prerequisite for further analysis. Key phrase extraction is the second correct feature because it extracts important terms from the text, directly addressing the requirement to 'extract key phrases' after language identification.
What should I do if I get this AI-102 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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