AI-102 Practice Question: Implement natural language processing solutions
A company wants to use Azure AI Language to automatically summarize large documents. The summarization must extract the most important sentences from each document. Which feature should they use?
⚠ Common exam trap
Test-takers frequently confuse 'key phrase extraction' with summarization because both involve identifying important content, but key phrase extraction returns only isolated terms, not coherent sentences, which fails the requirement for a sentence-based summary.
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
✓
Extractive summarization
Extractive summarization selects the most important sentences directly from the source document to create a concise summary, preserving the original wording. This aligns with the requirement to extract key sentences without generating new text, 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.
- ✓
Extractive summarization
Why this is correct
Extracts important sentences.
- ✗
Abstractive summarization
Why it's wrong here
Generates new sentences.
- ✗
Key phrase extraction
Why it's wrong here
Extracts key phrases, not sentences.
- ✗
Entity recognition
Why it's wrong here
Extracts named entities.
Go deeper
Related to this question
About these practice questions
This AI-102 question is part of Courseiva's 945-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
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.