Question 451 of 988

Implement natural language processing solutions →hardMultiple ChoiceObjective-mapped

Quick Answer

The answer is to identify entities in the text and link them to a knowledge base. This is the core purpose of entity linking in Azure AI Language: it goes beyond simple named entity recognition (NER) by disambiguating and connecting each detected entity—such as a person, place, or organization—to a unique, well-known identifier in a knowledge base like Wikipedia or Microsoft’s own Bing entity graph. On the Microsoft Azure AI Engineer Associate AI-102 exam, this question tests your ability to distinguish entity linking from other Azure AI Language features like NER, key phrase extraction, or sentiment analysis, which are common distractors. A frequent trap is confusing entity linking with NER, but remember that NER only extracts and classifies entities without providing a knowledge base reference. For a quick memory tip, think of the word “link” in entity linking as the clue: it always connects to an external knowledge base, not just labels the text.

AI-102 Practice Question: Implement natural language processing solutions

This AI-102 practice question tests your understanding of implement natural language processing 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

{
  "kind": "EntityLinking",
  "parameters": {
    "modelVersion": "latest"
  },
  "analysisInput": {
    "documents": [
      {
        "id": "1",
        "language": "en",
        "text": "Microsoft Azure provides AI services."
      }
    ]
  }
}

Refer to the exhibit. You are calling the Azure AI Language API for entity linking. What is the primary purpose of this request?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "primary"
Why it matters: Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.

Question 1hardmultiple choice

Full question →

Exhibit

{
  "kind": "EntityLinking",
  "parameters": {
    "modelVersion": "latest"
  },
  "analysisInput": {
    "documents": [
      {
        "id": "1",
        "language": "en",
        "text": "Microsoft Azure provides AI services."
      }
    ]
  }
}

A
To identify entities in the text and link them to a knowledge base.
Entity linking maps entities to known entities in a knowledge base.
B
To extract named entities from the text without linking.
Why wrong: That is NER, not entity linking.
C
To extract key phrases from the text.
Why wrong: Key phrase extraction is a different API.
D
To analyze the sentiment of the text.
Why wrong: Sentiment analysis is a different API.

Full breakdown with real-world context →

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

✓

To identify entities in the text and link them to a knowledge base.

Option A is correct because entity linking identifies named entities and links them to a knowledge base (like Wikipedia). Option B is wrong because entity extraction without linking is done by NER. Option C is wrong because key phrase extraction is a different API. Option D is wrong because sentiment analysis is separate.

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.

✓
To identify entities in the text and link them to a knowledge base.
Why this is correct
Entity linking maps entities to known entities in a knowledge base.
Clue confirmation
The clue word "primary" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
To extract named entities from the text without linking.
Why it's wrong here
That is NER, not entity linking.
✗
To extract key phrases from the text.
Why it's wrong here
Key phrase extraction is a different API.
✗
To analyze the sentiment of the text.
Why it's wrong here
Sentiment analysis is a different API.

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.

Trap categories for this question

Keyword trap
Key phrase extraction is a different API.

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 natural language processing solutions — This question tests Implement natural language processing solutions — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: To identify entities in the text and link them to a knowledge base. — Option A is correct because entity linking identifies named entities and links them to a knowledge base (like Wikipedia). Option B is wrong because entity extraction without linking is done by NER. Option C is wrong because key phrase extraction is a different API. Option D is wrong because sentiment analysis is separate.

What should I do if I get this AI-102 question wrong?

Are there clue words in this question I should notice?

Yes — watch for: "primary". Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.

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

Question Discussion

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