Describe features of Natural Language Processing workloads on Azure →easyMultiple ChoiceObjective-mapped
Key Phrase Extraction for Main Topics in Articles
A news agency publishes hundreds of articles daily. They want to automatically determine the main topics discussed in each article, such as 'politics', 'economy', or 'sports', without manually tagging them. The agency has no labeled training data. Which built-in Azure AI Language feature should they use?
Quick Answer
The answer is key phrase extraction, because it automatically identifies the main topics or themes in a document without requiring any labeled training data. This built-in Azure AI Language feature analyzes unstructured text and returns a list of key phrases—such as ‘politics’, ‘economy’, or ‘sports’—that represent the document’s central ideas, making it ideal for the news agency’s need to determine main topics without manual tagging. On the AI-900 exam, this question tests your understanding of Azure AI Language’s prebuilt capabilities, specifically distinguishing key phrase extraction from other features like entity recognition or sentiment analysis. A common trap is confusing it with named entity recognition, which extracts specific people, places, or organizations rather than overarching themes. Remember: key phrase extraction is for *themes* and *topics*, not specific entities. For a quick memory tip, think “Key phrases = Key topics,” and recall that it works out-of-the-box with zero training data.
⚠ Common exam trap
Candidates often confuse key phrase extraction with named entity recognition, but NER extracts specific named entities (e.g., 'Microsoft', 'Seattle') rather than general topic phrases, making it unsuitable for identifying broad themes like 'politics' or 'sports'.
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
✓
Key phrase extraction
Key phrase extraction is the correct choice because it automatically identifies the main topics or themes in a document without requiring any labeled training data. The news agency can use this built-in Azure AI Language feature to extract key phrases like 'politics', 'economy', or 'sports' from each article, enabling automatic topic categorization without manual tagging.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Sentiment analysis
Why it's wrong here
Sentiment analysis evaluates whether text is positive, negative, or neutral, not the topics discussed.
- ✓
Key phrase extraction
Why this is correct
Key phrase extraction extracts the main topics or key points from text without requiring training data.
- ✗
Named entity recognition
Why it's wrong here
Named entity recognition identifies specific named entities like people, organizations, and locations, not general topics.
- ✗
Language detection
Why it's wrong here
Language detection identifies the language of the text, not its topics.
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Azure Machine Learning Studio
Key term
Azure AI Language
Azure AI Language is a cloud-based service from Microsoft that uses natural language processing to understand, analyze, and generate human language for applications.
Key term
Feature
A feature is a distinct unit of functionality that delivers value to the user, often managed and tracked throughout the software development lifecycle.
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Same concept, more angles
1 more way this is tested on AI-900
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 news agency publishes hundreds of articles daily. They want to automatically extract the main topics discussed in each article, such as 'politics', 'economy', or 'sports', to categorize content without manual tagging. Which built-in Azure AI Language feature should they use?
easy- ✓ A.Key phrase extraction
- B.Named entity recognition
- C.Sentiment analysis
- D.Language detection
Why A: Key phrase extraction is the correct choice because it identifies the main topics or subjects discussed in a document, such as 'politics', 'economy', or 'sports', without requiring manual tagging. This feature returns a list of key phrases that represent the core content of each article, directly addressing the need to automatically categorize content by topic.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-900 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-900 exam.