- A
Azure AI Translator and Azure AI Search
Why wrong: Translation is not needed; search does not extract issues or sentiment.
- B
Azure AI Speech and Azure AI Search
Why wrong: Azure AI Speech transcribes audio but doesn't analyze text; Azure AI Search indexes but doesn't extract insights.
- C
Azure AI Document Intelligence and Azure AI Language
Why wrong: Document Intelligence is for layout-based documents, not call transcripts.
- D
Azure AI Language (key phrase extraction, entity recognition, sentiment analysis)
Azure AI Language provides built-in capabilities for extracting issues, resolutions, and sentiment from text.
Question 626 of 993
Implement knowledge mining and information extraction solutions →easyMultiple ChoiceObjective-mapped
AI-102 Practice Question: Implement knowledge mining and information extraction solutions
This AI-102 practice question tests your understanding of implement knowledge mining and information extraction solutions. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 building a knowledge mining solution to extract insights from customer support call transcripts. The solution must identify the customer's issue, the resolution provided, and the sentiment of the call. Which combination of Azure AI services should you use?
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 (key phrase extraction, entity recognition, sentiment analysis)
Option D is correct because Azure AI Language provides the specific capabilities needed: key phrase extraction to identify the customer's issue, entity recognition to identify the resolution, and sentiment analysis to determine the call sentiment. These are all built-in features of the Language service, making it the single-service solution for this knowledge mining task.
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.
- ✗
Azure AI Translator and Azure AI Search
Why it's wrong here
Translation is not needed; search does not extract issues or sentiment.
- ✗
Azure AI Speech and Azure AI Search
Why it's wrong here
Azure AI Speech transcribes audio but doesn't analyze text; Azure AI Search indexes but doesn't extract insights.
- ✗
Azure AI Document Intelligence and Azure AI Language
Why it's wrong here
Document Intelligence is for layout-based documents, not call transcripts.
- ✓
Azure AI Language (key phrase extraction, entity recognition, sentiment analysis)
Why this is correct
Azure AI Language provides built-in capabilities for extracting issues, resolutions, and sentiment from text.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
This question tests the misconception that multiple services are needed for a task that a single service can handle, leading candidates to overcomplicate the solution with unnecessary combinations like Speech + Search or Document Intelligence + Language.
Detailed technical explanation
How to think about this question
Azure AI Language's key phrase extraction uses a statistical model to identify the most salient points in text, which maps to the customer's issue. Entity recognition can identify resolution-related entities (e.g., 'refund', 'reset password') using a pre-built or custom model. Sentiment analysis scores each sentence and the overall document on a scale from 0 (negative) to 1 (positive), with neutral scores for factual statements. In a real-world scenario, you would preprocess the transcript with Azure AI Speech for transcription, then feed the text to Azure AI Language for extraction and analysis.
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
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this AI-102 question test?
Implement knowledge mining and information extraction solutions — This question tests Implement knowledge mining and information extraction solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure AI Language (key phrase extraction, entity recognition, sentiment analysis) — Option D is correct because Azure AI Language provides the specific capabilities needed: key phrase extraction to identify the customer's issue, entity recognition to identify the resolution, and sentiment analysis to determine the call sentiment. These are all built-in features of the Language service, making it the single-service solution for this knowledge mining task.
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.
About these practice questions
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Last reviewed: Jul 4, 2026
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