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Implement natural language processing solutionshardMultiple ChoiceObjective-mapped

AI-102 Practice Question: Implement natural language processing solutions

You are designing an NLP solution to analyze legal documents. The solution must identify specific clauses and parties involved. Which Azure AI service is most appropriate?

⚠ Common exam trap

Many candidates confuse Pre-built NER with Custom NER, assuming the pre-built model can handle domain-specific entities like legal clauses, but it only recognizes generic categories and cannot be retrained.

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

Custom Named Entity Recognition in Azure AI Language

Custom Named Entity Extraction (Custom NER) in Azure AI Language is the correct choice because it allows you to train a model to recognize domain-specific entities like legal clauses and party names from your own labeled data. Pre-built NER only recognizes generic entity types (e.g., person, organization, location) and cannot be customized for legal terminology. This makes Custom NER the only option that meets the requirement to identify specific clauses and parties unique to legal documents.

Answer analysis

Option-by-option breakdown

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

  • Custom Named Entity Recognition in Azure AI Language

    Why this is correct

    Custom NER can be trained to recognize domain-specific entities.

  • Pre-built Named Entity Recognition in Azure AI Language

    Why it's wrong here

    Pre-built NER only recognizes common entities.

  • Text Analytics for Health

    Why it's wrong here

    Text Analytics for Health is for medical data.

  • Immersive Reader

    Why it's wrong here

    Immersive Reader is for reading support.

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