Implement knowledge mining and information extraction solutions →mediumMultiple ChoiceObjective-mapped
AI-102 Practice Question: Implement knowledge mining and information extraction solutions
Your organization has a knowledge base of technical manuals in PDF format. You need to enable users to ask natural language questions and get answers from the manuals. Which solution should you build?
⚠ Common exam trap
Many candidates confuse retrieval (search) with extraction (question answering), assuming that any solution involving Azure AI Search or GPT-4o is automatically the best for Q&A, when in fact custom question answering is the purpose-built service for direct answer extraction from documents.
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 Language custom question answering with the documents as sources
Azure AI Language custom question answering is specifically designed to ingest documents (like PDFs) and provide a natural language Q&A interface over them. It uses a built-in extractive reader to find answer spans directly from the source text, making it the most straightforward solution for answering questions from a static knowledge base of technical manuals without requiring additional search or vectorization infrastructure.
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 Search with integrated vectorization and semantic search
Why it's wrong here
Search returns documents, not direct answers.
- ✗
Azure OpenAI Service with GPT-4o and Azure AI Search as a data source
Why it's wrong here
This option fails because Azure AI Search, whilst capable of indexing text from PDFs, lacks the advanced document intelligence required to robustly parse complex technical manuals, extract structured information, or handle diverse layouts effectively for optimal retrieval augmented generation. It is tempting because Azure OpenAI Service with GPT-4o and Azure AI Search forms the core RAG pattern for natural language querying over *already processed* or text-based custom data, making it the correct choice when the data is pre-extracted or inherently text-centric.
- ✓
Azure AI Language custom question answering with the documents as sources
Why this is correct
Provides direct answers from documents.
- ✗
Azure AI Document Intelligence to extract text and then use Azure AI Search
Why it's wrong here
No Q&A capability.
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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.