AI-102 Practice Question: Implement knowledge mining and document intelligence solutions
A healthcare organization uses Azure Document Intelligence to process patient intake forms. They notice that the confidence scores for field extraction are low. What is the most likely cause?
⚠ Common exam trap
Many exam-takers confuse low confidence with OCR or resolution issues, but the exam tests the specific requirement for sufficient labeled training data in custom models, not generic document quality problems.
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
✓
The custom model was trained with only 10 labeled forms
Custom models in Azure Document Intelligence require a minimum of five labeled forms for training, but low confidence scores typically indicate insufficient training data. With only 10 labeled forms, the model lacks enough examples to generalize well across variations in handwriting, formatting, and field values, leading to poor extraction confidence.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The document resolution is too low
Why it's wrong here
Low resolution can affect OCR but not the primary cause of low confidence.
- ✗
The document layout is not analyzed
Why it's wrong here
Layout analysis is always performed; it does not affect confidence scores.
- ✓
The custom model was trained with only 10 labeled forms
Why this is correct
Custom models require at least 5 labeled forms; more samples improve confidence.
- ✗
The batch processing size is too large
Why it's wrong here
Batch size does not affect confidence scores.
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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.