Question 271 of 988
Implement natural language processing solutionsmediumMultiple SelectObjective-mapped

AI-102 Practice Question: Implement natural language processing solutions

This AI-102 practice question tests your understanding of implement natural language processing solutions. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.

Which THREE actions should an engineer take when deploying a custom question answering project in Azure Cognitive Service for Language?

Question 1mediummulti select
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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

Set up a multi-turn extraction policy for follow-up questions.

Option B is correct because multi-turn extraction is a core feature of custom question answering that allows the system to handle follow-up questions by maintaining context across turns. This is essential for conversational flows where a user's subsequent query depends on the previous answer, and it is configured via the project settings in Language Studio.

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.

  • Integrate LUIS for intent detection.

    Why it's wrong here

    Question answering has its own intent detection.

  • Set up a multi-turn extraction policy for follow-up questions.

    Why this is correct

    Multi-turn extraction is needed for conversation flow.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Enable active learning to improve answer suggestions.

    Why this is correct

    Active learning helps refine the model.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Add chit-chat to handle common conversational phrases.

    Why this is correct

    Chit-chat improves user experience.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Configure a single-turn extraction policy.

    Why it's wrong here

    Single-turn does not handle follow-up questions.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates often confuse the need for LUIS integration (Option A) with question answering, not realizing that custom question answering is a standalone service that does not require intent detection from LUIS.

Detailed technical explanation

How to think about this question

Under the hood, multi-turn extraction works by analyzing the conversation history and using a 'prompt' field in the QnA pairs to define follow-up questions and their associated answers. This is implemented via the 'context' property in the REST API, where each QnA pair can have a 'context' object with 'prompts' that specify the follow-up queries and their display order, enabling stateful dialog management without external orchestration.

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 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: Set up a multi-turn extraction policy for follow-up questions. — Option B is correct because multi-turn extraction is a core feature of custom question answering that allows the system to handle follow-up questions by maintaining context across turns. This is essential for conversational flows where a user's subsequent query depends on the previous answer, and it is configured via the project settings in Language Studio.

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: Jun 11, 2026

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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.