The answer is that the suggester’s sourceFields do not include the “people” or “organizations” fields. This is the most likely reason because a suggester in Azure AI Search only generates suggestions from the fields explicitly listed in its sourceFields property; if the index definition created with PowerShell only specifies “content” as a source field, then partial name searches against entity fields like “people” or “organizations” will return no results. On the Microsoft Azure AI Engineer Associate AI-102 exam, this question tests your understanding of how suggesters are configured for knowledge mining solutions, often appearing as a trap where you must verify that the sourceFields match the fields users actually query. A common mistake is assuming the suggester automatically covers all string fields, but it does not—you must explicitly include each field. Memory tip: “SourceFields must match search fields—if users type a name, the suggester needs that field in its list.”
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. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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.
$index = @{
name = "knowledge-index"
fields = @(
@{name = "id"; type = "Edm.String"; key = $true},
@{name = "content"; type = "Edm.String"; searchable = $true},
@{name = "people"; type = "Collection(Edm.String)"; searchable = $true; filterable = $true},
@{name = "organizations"; type = "Collection(Edm.String)"; searchable = $true; filterable = $true}
)
suggesters = @(
@{name = "sg"; searchMode = "analyzingInfixMatching"; sourceFields = @("content")}
)
}
You are reviewing an index definition created with PowerShell. The index is used for a knowledge mining solution that extracts people and organizations from documents. Users report that when they type partial names in the search bar, the suggester does not return suggestions. 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 suggester sourceFields do not include people or organizations
Option C is correct because the suggester's sourceFields only include "content", not the "people" or "organizations" fields. Users likely want suggestions from those entity fields. Option A is wrong because the key field is required and correct. Option B is wrong because the suggester mode is valid. Option D is wrong because the fields are correctly defined as collections.
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 people and organizations fields should be Edm.String instead of Collection(Edm.String)
Why it's wrong here
Collection is correct for multiple values.
✗
The id field is not defined as a key in the index
Why it's wrong here
The key is correctly set to true.
✓
The suggester sourceFields do not include people or organizations
Why this is correct
Suggestions are only generated from the content field.
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 suggester searchMode should be 'analyzingInfixMatching' which is incorrect
Why it's wrong here
The mode is valid.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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 AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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: The suggester sourceFields do not include people or organizations — Option C is correct because the suggester's sourceFields only include "content", not the "people" or "organizations" fields. Users likely want suggestions from those entity fields. Option A is wrong because the key field is required and correct. Option B is wrong because the suggester mode is valid. Option D is wrong because the fields are correctly defined as collections.
What should I do if I get this AI-102 question wrong?
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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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