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AI-102 Practice Question: Implement natural language processing solutions

You are using Azure AI Language to analyze medical records. The built-in NER model does not recognize some medical terms. What should you do?

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

Train a custom NER model using Azure AI Language

Custom NER allows training a model on your specific terms. Text Analytics for Health is a specialized built-in model for healthcare but may not cover all custom terms. Custom Text Classification is for document classification. Entity Linking disambiguates to a knowledge base.

Answer analysis

Option-by-option breakdown

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

  • Use the Text Analytics for Health feature

    Why it's wrong here

    Text Analytics for Health is a pre-built model; it may not include the specific terms you need.

  • Use Entity Linking

    Why it's wrong here

    Entity Linking links entities to a knowledge base, not for custom terms.

  • Use Custom Text Classification

    Why it's wrong here

    Custom Text Classification is for classifying documents, not extracting entities.

  • Train a custom NER model using Azure AI Language

    Why this is correct

    Custom NER can be trained on your specific medical terms.

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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.