Implement knowledge mining and information extraction solutions →easyMultiple ChoiceObjective-mapped
AI-102 Practice Question: Implement knowledge mining and information extraction solutions
You are building a knowledge mining solution to extract key information from handwritten forms. The forms contain checkboxes, signatures, and handwritten text. Which Azure AI service should you use?
⚠ Common exam trap
Many candidates confuse Azure AI Vision OCR (which handles printed text) with Document Intelligence's layout model (which handles handwritten text, checkboxes, and signatures), leading them to choose option C incorrectly.
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
✓
Azure AI Document Intelligence layout model
Azure AI Document Intelligence's layout model is designed to extract text, tables, checkboxes, signatures, and structure from documents, including handwritten forms. It combines OCR with deep learning models to understand the spatial relationships between elements, making it the correct choice for this scenario.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure AI Language
Why it's wrong here
Azure AI Language is for text analytics, not handwriting recognition.
- ✗
Azure AI Speech
Why it's wrong here
Azure AI Speech is for speech-to-text, not handwriting.
- ✗
Azure AI Vision OCR
Why it's wrong here
OCR extracts printed text but does not handle checkboxes or signatures as form fields.
- ✓
Azure AI Document Intelligence layout model
Why this is correct
The layout model extracts checkboxes, signatures, and handwritten text from forms.
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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.