The answer is a missing or incorrectly defined output field mapping in the indexer. While the skillset itself runs successfully, the output field mapping is the critical bridge that directs a skill’s output—like the sentiment score from the Sentiment skill—into a specific field in the search index. Without this mapping, the indexer has no instruction on where to place the enriched data, so the 'sentiment' field remains empty even though the skill processed the content. On the Microsoft Azure AI Engineer Associate AI-102 exam, this scenario tests your understanding of the indexer’s role in the enrichment pipeline, a common trap where candidates assume a successful skillset guarantees index population. Remember that the skillset enriches the document, but the indexer’s output field mappings are what actually write those enrichments to the index. A useful memory tip is “Skills enrich, indexers map”—if the skill runs but data is missing, always check the indexer’s output field mappings first.
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 using Azure AI Search to build a knowledge base for a customer support portal. The index includes a 'sentiment' field that should be populated using the Sentiment skill. However, the sentiment scores are not being written to the index. The skillset runs successfully. 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.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The output field mapping for 'sentiment' is missing or incorrectly defined in the indexer.
Option C is correct: the output field mapping in the indexer is missing or incorrect. Option A is incorrect because the skill ran successfully. Option B is incorrect because the sentiment skill does not require a specific data type. Option D is incorrect because indexer execution is successful.
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 output field mapping for 'sentiment' is missing or incorrectly defined in the indexer.
Why this is correct
Without mapping, skill output is not written to index.
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 Sentiment skill is not correctly configured in the skillset.
Why it's wrong here
Skill ran successfully, so configuration is correct.
✗
The indexer is in a failed state and not processing documents.
Why it's wrong here
Indexer runs successfully.
✗
The sentiment field in the index is of type 'Collection(Edm.String)' but the skill outputs a double.
Why it's wrong here
Type mismatch would cause skill error, not silent failure.
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 output field mapping for 'sentiment' is missing or incorrectly defined in the indexer. — Option C is correct: the output field mapping in the indexer is missing or incorrect. Option A is incorrect because the skill ran successfully. Option B is incorrect because the sentiment skill does not require a specific data type. Option D is incorrect because indexer execution is successful.
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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