AI-102 Practice Question: Implement natural language processing solutions
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.)
⚠ Common exam trap
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.
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.
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.
- ✗
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.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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