Question 491 of 993

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. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
{
  "skillset": {
    "name": "demo-skillset",
    "description": "Custom skillset for enrichment",
    "skills": [
      {
        "@odata.type": "#Microsoft.Skills.Custom.WebApiSkill",
        "name": "custom-skill",
        "description": "Calls external API for entity extraction",
        "uri": "https://myfunctionapp.azurewebsites.net/api/extract",
        "context": "/document",
        "inputs": [
          {
            "name": "text",
            "source": "/document/content"
          }
        ],
        "outputs": [
          {
            "name": "entities",
            "targetName": "extractedEntities"
          }
        ],
        "httpMethod": "POST",
        "timeout": "PT30S",
        "batchSize": 5,
        "degreeOfParallelism": 3
      }
    ]
  }
}

You have defined the custom WebApiSkill shown in the exhibit. The skill calls an Azure Function that can process up to 10 documents per second. However, you notice that the skill is failing with 429 errors. 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.
{
  "skillset": {
    "name": "demo-skillset",
    "description": "Custom skillset for enrichment",
    "skills": [
      {
        "@odata.type": "#Microsoft.Skills.Custom.WebApiSkill",
        "name": "custom-skill",
        "description": "Calls external API for entity extraction",
        "uri": "https://myfunctionapp.azurewebsites.net/api/extract",
        "context": "/document",
        "inputs": [
          {
            "name": "text",
            "source": "/document/content"
          }
        ],
        "outputs": [
          {
            "name": "entities",
            "targetName": "extractedEntities"
          }
        ],
        "httpMethod": "POST",
        "timeout": "PT30S",
        "batchSize": 5,
        "degreeOfParallelism": 3
      }
    ]
  }
}

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 degreeOfParallelism of 3 causes too many concurrent requests, exceeding the function's capacity

Option D is correct because the `degreeOfParallelism` of 3 causes the AI Search enrichment pipeline to invoke the Azure Function with up to 3 concurrent batches, each of size 5, resulting in up to 15 documents per second. Since the function can only handle 10 documents per second, this exceeds its capacity and triggers HTTP 429 (Too Many Requests) errors.

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 timeout of 30 seconds is too short for the function to respond

    Why it's wrong here

    The function processes quickly; timeout is not the issue.

  • The batch size of 5 is too large, causing the function to receive too many documents at once

    Why it's wrong here

    Batch size of 5 is fine; the issue is concurrency.

  • The context '/document' is incorrect, causing all documents to be processed as one

    Why it's wrong here

    Context is correct for per-document processing.

  • The degreeOfParallelism of 3 causes too many concurrent requests, exceeding the function's capacity

    Why this is correct

    With batchSize 5 and degreeOfParallelism 3, up to 15 documents are sent concurrently.

    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

The trap here is that candidates often focus on the batch size as the sole cause of rate limiting, overlooking that `degreeOfParallelism` multiplies the effective request rate, which is the actual trigger for 429 errors.

Detailed technical explanation

How to think about this question

Under the hood, the `degreeOfParallelism` property in a custom WebApiSkill controls how many concurrent calls the AI Search enrichment pipeline makes to the skill endpoint. Even with a modest batch size, a high parallelism value can overwhelm a downstream service that has its own rate limits. In practice, you must tune both `batchSize` and `degreeOfParallelism` to match the throughput of the Azure Function, often by testing with the function's concurrency limits and monitoring 429 responses to adjust retry policies.

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: The degreeOfParallelism of 3 causes too many concurrent requests, exceeding the function's capacity — Option D is correct because the `degreeOfParallelism` of 3 causes the AI Search enrichment pipeline to invoke the Azure Function with up to 3 concurrent batches, each of size 5, resulting in up to 15 documents per second. Since the function can only handle 10 documents per second, this exceeds its capacity and triggers HTTP 429 (Too Many Requests) errors.

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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Last reviewed: Jul 4, 2026

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