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AI-102 Practice Question: Implement knowledge mining and document intelligence solutions

A company is building a knowledge mining solution using Azure AI Search. They need to extract key phrases from a large set of documents in multiple languages. Which skill should they add to the skillset?

⚠ Common exam trap

It's easy for candidates to confuse Entity Recognition (which extracts single-word entities like 'Microsoft') with Key Phrase Extraction (which extracts multi-word phrases like 'Azure AI Search'), leading them to choose Option D instead of A.

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

Key Phrase Extraction skill

The Key Phrase Extraction skill is the correct choice because it is specifically designed to identify and extract the most important phrases from text, which directly supports the requirement to extract key phrases from documents. Azure AI Search's built-in Key Phrase Extraction skill leverages natural language processing to analyze text and return a list of key phrases, making it the appropriate skill for this knowledge mining solution.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Key Phrase Extraction skill

    Why this is correct

    Key Phrase Extraction is designed to extract key phrases from text.

  • Sentiment Analysis skill

    Why it's wrong here

    Sentiment Analysis evaluates sentiment, not key phrases.

  • Language Detection skill

    Why it's wrong here

    Language Detection only identifies the language, not key phrases.

  • Entity Recognition skill

    Why it's wrong here

    Entity Recognition identifies named entities, not key phrases.

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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