Summarizing Documents by Extracting Key Sentences with Azure AI Language
A news organization wants to automatically summarize long articles into short, coherent summaries. The solution must preserve the original meaning and key points. Which Azure AI service should be used?
Quick Answer
The answer is Azure AI Language’s extractive summarization capability. This service performs extractive summarization of documents by analyzing the input text and selecting the most salient sentences that preserve the original meaning and key points, making it ideal for automatically condensing long articles into coherent summaries. On the Microsoft Azure AI Engineer Associate AI-102 exam, this question tests your ability to distinguish between Azure AI Language’s text analysis features—specifically, extractive summarization versus key phrase extraction, which only pulls out isolated terms rather than full sentences. A common trap is confusing extractive summarization with Azure AI Translator (for language translation) or Azure AI Document Intelligence (for form parsing). Remember the memory tip: “Extract sentences, not phrases” to keep extractive summarization distinct from key phrase extraction when you see summarization tasks on the exam.
⚠ Common exam trap
It's easy for candidates to confuse Key Phrase Extraction (Option B) with summarization, but Key Phrase Extraction only returns isolated terms, not a coherent summary, whereas Extractive Summarization returns full sentences that preserve meaning.
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 - Extractive Summarization
Azure AI Language's Extractive Summarization is specifically designed to generate concise summaries by extracting the most important sentences from a document while preserving the original meaning and key points. This service uses natural language processing to rank sentences based on relevance and coherence, making it ideal for summarizing long articles without altering the original content.
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
Why it's wrong here
Document Intelligence extracts data from forms and documents, not summarization.
- ✗
Azure AI Language - Key Phrase Extraction
Why it's wrong here
Key phrase extraction extracts important phrases, not a coherent summary.
- ✓
Azure AI Language - Extractive Summarization
Why this is correct
Extractive summarization picks key sentences to form a summary.
- ✗
Azure AI Translator
Why it's wrong here
Translator is for language translation, not summarization.
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Same concept, more angles
1 more way this is tested on AI-102
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. 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?
easy- ✓ A.Extractive summarization
- B.Abstractive summarization
- C.Key phrase extraction
- D.Entity recognition
Why A: 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.
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.