ARM Template Kind for Custom Question Answering — Resource Provisioning
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 deploy the ARM template above to create an Azure AI Language resource. After deployment, you try to use the custom question answering feature but it is not available. What is the most likely reason?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The 'kind' property is set to 'TextAnalytics', which does not enable custom question answering.
The 'kind' property in the ARM template is set to 'TextAnalytics', which provisions a general-purpose Text Analytics resource. Custom question answering is a feature of the Azure AI Language service that requires the resource to be created with the 'kind' set to 'Language' or 'ConversationalLanguageUnderstanding' (depending on the API version). Because the resource is of the wrong kind, the custom question answering capability is not available, even though the deployment succeeds.
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.
✗
The apiVersion is too old to support custom question answering.
Why it's wrong here
2023-05-01 supports custom question answering.
✓
The 'kind' property is set to 'TextAnalytics', which does not enable custom question answering.
Why this is correct
TextAnalytics kind does not include custom question answering.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The SKU is set to S, but custom question answering requires a higher SKU.
Why it's wrong here
S SKU supports custom question answering.
✗
The location does not support custom question answering.
Why it's wrong here
Most regions support it.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume the feature is missing due to an outdated API version or insufficient SKU, when in fact the root cause is the incorrect resource 'kind' property, which is a subtle but critical distinction in Azure AI resource provisioning.
Detailed technical explanation
How to think about this question
Under the hood, the Azure AI Language service uses a unified resource model where the 'kind' property determines which sub-capabilities are enabled. Custom question answering relies on the 'Language' kind, which includes the question answering API endpoint and the ability to create and manage knowledge bases via the Language Studio. If the 'kind' is 'TextAnalytics', the resource only exposes endpoints for sentiment analysis, key phrase extraction, and similar features, and the question answering API is not registered in the resource's service principal. In a real-world scenario, a developer might accidentally reuse an existing Text Analytics template for a new project, leading to this exact issue.
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.
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: The 'kind' property is set to 'TextAnalytics', which does not enable custom question answering. — The 'kind' property in the ARM template is set to 'TextAnalytics', which provisions a general-purpose Text Analytics resource. Custom question answering is a feature of the Azure AI Language service that requires the resource to be created with the 'kind' set to 'Language' or 'ConversationalLanguageUnderstanding' (depending on the API version). Because the resource is of the wrong kind, the custom question answering capability is not available, even though the deployment succeeds.
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.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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