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

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.

Exhibit

Refer to the exhibit.
{
  "skills": [
    {
      "@odata.type": "#Microsoft.Skills.Text.SplitSkill",
      "name": "split",
      "context": "/document",
      "textSplitMode": "pages",
      "maximumPageLength": 5000,
      "pageOverlapLength": 500,
      "inputs": [
        { "name": "text", "source": "/document/content" }
      ],
      "outputs": [
        { "name": "textItems", "targetName": "pages" }
      ]
    },
    {
      "@odata.type": "#Microsoft.Skills.Text.EntityRecognitionSkill",
      "name": "entities",
      "context": "/document/pages/*",
      "categories": [ "Person", "Organization" ],
      "inputs": [
        { "name": "text", "source": "/document/pages/*" }
      ],
      "outputs": [
        { "name": "entities", "targetName": "entities" }
      ]
    }
  ]
}

You have the above skillset in Azure AI Search. The indexer processes a document with 12,000 characters of content. How many entity recognition skill executions occur?

Exhibit

Refer to the exhibit.
{
  "skills": [
    {
      "@odata.type": "#Microsoft.Skills.Text.SplitSkill",
      "name": "split",
      "context": "/document",
      "textSplitMode": "pages",
      "maximumPageLength": 5000,
      "pageOverlapLength": 500,
      "inputs": [
        { "name": "text", "source": "/document/content" }
      ],
      "outputs": [
        { "name": "textItems", "targetName": "pages" }
      ]
    },
    {
      "@odata.type": "#Microsoft.Skills.Text.EntityRecognitionSkill",
      "name": "entities",
      "context": "/document/pages/*",
      "categories": [ "Person", "Organization" ],
      "inputs": [
        { "name": "text", "source": "/document/pages/*" }
      ],
      "outputs": [
        { "name": "entities", "targetName": "entities" }
      ]
    }
  ]
}

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

✓

3

The Azure AI Search entity recognition skill has a maximum text length per execution of 5,000 characters. A document with 12,000 characters is split into chunks of up to 5,000 characters, resulting in three chunks (5,000 + 5,000 + 2,000). Each chunk triggers one skill execution, so three executions occur.

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.

  • ✗

    4

    Why it's wrong here

    The split produces exactly 3 pages for 12000 characters.

  • ✗

    2

    Why it's wrong here

    12000 characters produce 3 pages due to overlap.

  • ✓

    3

    Why this is correct

    Three pages result from the split, each triggering an entity recognition execution.

    Related concept

    Read the scenario before looking for a memorised answer.

  • ✗

    1

    Why it's wrong here

    The split skill produces multiple pages; the entity skill runs per page.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The Azure AI Search entity recognition skill has a maximum text length per execution of 5,000 characters. Candidates might incorrectly divide 12,000 by 5,000 and round down to 2, or assume a single execution can handle the entire document, ignoring the chunking behavior.

Detailed technical explanation

How to think about this question

The entity recognition skill in Azure AI Search uses a character-based chunking strategy with a hard limit of 5,000 characters per skill invocation. This limit is documented in the skill reference and applies to all text-based cognitive skills. In practice, if a document exceeds this limit, the indexer automatically splits the text at natural boundaries (e.g., sentence or paragraph breaks) to avoid breaking words, but the total number of executions is determined by the ceiling of total characters divided by 5,000.

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.

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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: 3 — The Azure AI Search entity recognition skill has a maximum text length per execution of 5,000 characters. A document with 12,000 characters is split into chunks of up to 5,000 characters, resulting in three chunks (5,000 + 5,000 + 2,000). Each chunk triggers one skill execution, so three executions occur.

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.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jul 4, 2026

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This AI-102 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-102 exam.