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Implement knowledge mining and information extraction solutions →hardMultiple ChoiceObjective-mapped

Quick Answer

The answer is that the SplitSkill outputs are not correctly mapped to the SentimentSkill input, causing the sentiment skill to run only on the first page of each document. This occurs because the SplitSkill breaks each PDF into separate pages, and the SentimentSkill processes each page as an individual item; without proper output-to-input mapping, the sentiment skill defaults to the first page only, leaving the remaining 500 pages unscored. On the Microsoft Azure AI Engineer Associate AI-102 exam, this question tests your understanding of skillset execution flow and the critical role of field mappings in Azure AI Search enrichment pipelines, where a common trap is assuming the indexer automatically passes all split outputs to downstream skills. The search intent "split skill output mapping sentiment" highlights the precise failure point: when the `outputFieldMappings` from the SplitSkill's `pages` to the SentimentSkill's `text` are missing or incorrect, enrichment halts after the first split. Memory tip: think "split first, map every page" — if you don't map the split output, you only get one shot at sentiment.

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. 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.

Exhibit

Refer to the exhibit.

{
  "name": "my-skillset",
  "description": "Custom skillset",
  "skills": [
    {
      "@odata.type": "#Microsoft.Skills.Text.SplitSkill",
      "context": "/document",
      "textSplitMode": "pages",
      "maximumPageLength": 5000,
      "defaultLanguageCode": "en",
      "inputs": [
        { "name": "text", "source": "/document/content" }
      ],
      "outputs": [
        { "name": "textItems", "targetName": "pages" }
      ]
    },
    {
      "@odata.type": "#Microsoft.Skills.Text.V3.SentimentSkill",
      "context": "/document/pages/*",
      "defaultLanguageCode": "en",
      "inputs": [
        { "name": "text", "source": "/document/pages/*" }
      ],
      "outputs": [
        { "name": "sentiment", "targetName": "sentiment" }
      ]
    }
  ]
}

You are reviewing a skillset definition for an Azure AI Search indexer. The indexer is configured to index 1000 PDF documents. After running the indexer, you notice that only 500 documents have sentiment scores. 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.

Question 1hardmultiple choice
Full question →

Exhibit

Refer to the exhibit.

{
  "name": "my-skillset",
  "description": "Custom skillset",
  "skills": [
    {
      "@odata.type": "#Microsoft.Skills.Text.SplitSkill",
      "context": "/document",
      "textSplitMode": "pages",
      "maximumPageLength": 5000,
      "defaultLanguageCode": "en",
      "inputs": [
        { "name": "text", "source": "/document/content" }
      ],
      "outputs": [
        { "name": "textItems", "targetName": "pages" }
      ]
    },
    {
      "@odata.type": "#Microsoft.Skills.Text.V3.SentimentSkill",
      "context": "/document/pages/*",
      "defaultLanguageCode": "en",
      "inputs": [
        { "name": "text", "source": "/document/pages/*" }
      ],
      "outputs": [
        { "name": "sentiment", "targetName": "sentiment" }
      ]
    }
  ]
}

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

✓

The SplitSkill outputs are not correctly mapped to the SentimentSkill input; the skill runs only on the first page of each document

Option B is correct because the SplitSkill splits the document into pages, and the SentimentSkill runs per page. If the split output is not properly mapped, sentiment only runs on the first page. Option A is wrong because the skill order is correct (split before sentiment). Option C is wrong because the skill version is V3, which is valid. Option D is wrong because the context is correct.

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 skills are defined in the wrong order; sentiment should run before split

    Why it's wrong here

    Sentiment needs text; split must come first.

  • ✗

    The SentimentSkill is not supported in this region

    Why it's wrong here

    SentimentSkill is available globally.

  • ✓

    The SplitSkill outputs are not correctly mapped to the SentimentSkill input; the skill runs only on the first page of each document

    Why this is correct

    The context "/document/pages/*" should iterate over pages, but if split output is only one item, it only processes one page.

    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 context of the SentimentSkill should be "/document" instead of "/document/pages/*"

    Why it's wrong here

    Context "/document/pages/*" is correct for per-page sentiment.

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.

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FAQ

Questions learners often ask

What does this AI-102 question test?

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 SplitSkill outputs are not correctly mapped to the SentimentSkill input; the skill runs only on the first page of each document — Option B is correct because the SplitSkill splits the document into pages, and the SentimentSkill runs per page. If the split output is not properly mapped, sentiment only runs on the first page. Option A is wrong because the skill order is correct (split before sentiment). Option C is wrong because the skill version is V3, which is valid. Option D is wrong because the context is correct.

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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Last reviewed: Jun 20, 2026

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