AI-102 Practice Question: Implement natural language processing solutions
Your organization has a large corpus of legal documents that need to be analyzed for specific clauses. You need to extract key information such as party names, dates, and monetary amounts. The solution must be able to handle varying document formats (PDF, Word, scanned images). Which combination of Azure AI services should you use?
⚠ Common exam trap
Test-takers frequently confuse Azure AI Computer Vision's OCR capabilities with Document Intelligence's full document understanding, overlooking that Computer Vision lacks the ability to extract structured key-value pairs and custom entities without additional services.
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 and Custom Entity Extraction
Azure AI Document Intelligence (formerly Form Recognizer) is designed to extract text, structure, and key-value pairs from PDFs, Word documents, and scanned images using OCR and layout analysis. Combining it with Custom Entity Extraction (via Azure AI Language's custom NER) allows you to identify domain-specific entities like party names, dates, and monetary amounts across varying formats. This pairing directly addresses the need for both document parsing and tailored entity recognition.
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 Document Intelligence and Custom Entity Extraction
Why this is correct
Document Intelligence extracts text from various formats; Custom Entity Extraction identifies specific entities.
- ✗
Azure AI Computer Vision and Custom Entity Extraction
Why it's wrong here
Computer Vision lacks native capability for extracting structured entities like party names or monetary amounts from text, as it is designed for image analysis and OCR, not semantic parsing of legal clauses. This option is tempting because Computer Vision can handle scanned images and PDFs via OCR, and custom entity extraction suggests flexibility, but the correct solution requires Azure AI Language’s pre-built or custom named entity recognition, which directly identifies and categorises domain-specific terms from text, regardless of source format.
- ✗
Azure AI Translator and Custom Entity Extraction
Why it's wrong here
Translator is not needed; entity extraction alone doesn't process documents.
- ✗
Azure AI Speech and Custom Entity Extraction
Why it's wrong here
Speech is for audio, not text documents.
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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.