- A
Detect the language of the query using Azure AI Language and then use a generic analyzer
Why wrong: Generic analyzer does not provide language-specific improvements.
- B
Translate all queries to English using Azure AI Translator before searching
Why wrong: Translation may introduce errors and does not preserve original language results.
- C
Use a single non-language-specific analyzer like 'standard.lucene' for all documents
Why wrong: Standard Lucene analyzer does not handle language-specific features.
- D
Use language-specific analyzers in the Azure AI Search index for each language
Language analyzers provide stemming and stopword removal per language, improving search relevance.
Question 618 of 993
Implement knowledge mining and information extraction solutions →mediumMultiple 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. 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 building a knowledge mining solution that indexes technical manuals in multiple languages. The solution must enable users to search in their native language and retrieve results in the same language. Which approach 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
✓
Use language-specific analyzers in the Azure AI Search index for each language
Option D is correct because Azure AI Search supports language-specific analyzers (e.g., 'de.microsoft' for German, 'fr.microsoft' for French) that apply linguistic rules such as stemming, lemmatization, and stop-word removal tailored to each language. This ensures that queries and documents are processed in the same language, enabling users to search and retrieve results in their native language without translation loss.
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.
- ✗
Detect the language of the query using Azure AI Language and then use a generic analyzer
Why it's wrong here
Generic analyzer does not provide language-specific improvements.
- ✗
Translate all queries to English using Azure AI Translator before searching
Why it's wrong here
Translation may introduce errors and does not preserve original language results.
- ✗
Use a single non-language-specific analyzer like 'standard.lucene' for all documents
Why it's wrong here
Standard Lucene analyzer does not handle language-specific features.
- ✓
Use language-specific analyzers in the Azure AI Search index for each language
Why this is correct
Language analyzers provide stemming and stopword removal per language, improving search relevance.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume translation or generic analyzers are sufficient, overlooking that Azure AI Search's language-specific analyzers are designed to preserve linguistic integrity and meet the exact requirement of native-language search and retrieval without cross-language conversion.
Detailed technical explanation
How to think about this question
Azure AI Search uses Microsoft's proprietary analyzers (e.g., 'en.microsoft') and Lucene-based analyzers (e.g., 'de.lucene') that apply language-specific token filters like stemmers, lemmatizers, and decompounders. For example, the German analyzer 'de.microsoft' correctly splits 'Donaudampfschifffahrtsgesellschaft' into 'Donau', 'Dampf', 'Schifffahrt', 'Gesellschaft', while a generic analyzer would not. In a multi-language index, you can assign a different analyzer per field using the 'analyzer' property in the index schema, ensuring each language field is processed correctly.
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.
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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: Use language-specific analyzers in the Azure AI Search index for each language — Option D is correct because Azure AI Search supports language-specific analyzers (e.g., 'de.microsoft' for German, 'fr.microsoft' for French) that apply linguistic rules such as stemming, lemmatization, and stop-word removal tailored to each language. This ensures that queries and documents are processed in the same language, enabling users to search and retrieve results in their native language without translation loss.
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
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jul 4, 2026
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