CLU Runtime API Verbose Parameter — Enabling Entity Extraction
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.
Exhibit
Refer to the exhibit.
{
"kind": "Conversation",
"analysisInput": {
"conversationItem": {
"id": "1",
"text": "I need to book a flight to Seattle for next Monday.",
"modality": "text",
"language": "en"
}
},
"parameters": {
"projectName": "FlightBooking",
"deploymentName": "production"
}
}
You are debugging a CLU application. The JSON above shows a request to the Azure AI Language runtime API. The response returns an intent of "BookFlight" with a confidence of 0.95, but no entities are extracted. The training data includes entities like "Location" and "DateTime". What is the most likely cause?
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.
Exhibit
Refer to the exhibit.
{
"kind": "Conversation",
"analysisInput": {
"conversationItem": {
"id": "1",
"text": "I need to book a flight to Seattle for next Monday.",
"modality": "text",
"language": "en"
}
},
"parameters": {
"projectName": "FlightBooking",
"deploymentName": "production"
}
}
A
The deployment name is incorrect.
Why wrong: Deployment name is present and likely correct.
B
The model was not trained on entity extraction.
Why wrong: The training data includes entities.
C
The utterance does not contain any entities.
Why wrong: The utterance contains 'Seattle' and 'next Monday' which are entities.
D
The request is missing the 'verbose' parameter set to true.
Verbose parameter is required to get entity details.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The request is missing the 'verbose' parameter set to true.
Option D is correct because the CLU runtime API, by default, returns only the top intent and does not include extracted entities unless the 'verbose' query parameter is set to true. Without this parameter, the response omits the entities array even if the model was trained to extract them, which explains why the intent is returned with high confidence but no entities appear.
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 deployment name is incorrect.
Why it's wrong here
Deployment name is present and likely correct.
✗
The model was not trained on entity extraction.
Why it's wrong here
The training data includes entities.
✗
The utterance does not contain any entities.
Why it's wrong here
The utterance contains 'Seattle' and 'next Monday' which are entities.
✓
The request is missing the 'verbose' parameter set to true.
Why this is correct
Verbose parameter is required to get entity details.
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.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Azure often tests the misconception that a successful API response with a high-confidence intent implies all features (like entity extraction) are working correctly, when in fact the default response may omit entities unless a specific parameter is included.
Detailed technical explanation
How to think about this question
The CLU runtime API's default response schema includes only the top intent and its confidence score; the 'verbose' parameter (set to true) triggers the inclusion of all extracted entities, their values, and additional metadata like entity resolutions. This design reduces payload size for common use cases where only the intent is needed, but it can confuse developers who expect entities by default. In practice, always check the API documentation for default response fields and use the 'verbose' parameter when entity extraction is required.
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 request is missing the 'verbose' parameter set to true. — Option D is correct because the CLU runtime API, by default, returns only the top intent and does not include extracted entities unless the 'verbose' query parameter is set to true. Without this parameter, the response omits the entities array even if the model was trained to extract them, which explains why the intent is returned with high confidence but no entities appear.
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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