- A
Encrypting sensitive phrases in a document for secure storage
Why wrong: Encryption is a security operation — key phrase extraction identifies the most meaningful terms in text.
- B
Identifying the most important words and phrases that best represent a text's main topics
Key phrase extraction surfaces the key concepts in text — enabling topic summarisation, tagging, and content understanding.
- C
Finding and extracting password-like phrases from user messages for security monitoring
Why wrong: Credential detection is a security feature — key phrase extraction identifies topically important terms, not sensitive data.
- D
Selecting the highest-scoring responses from a list of candidate answers
Why wrong: Answer selection is question answering — key phrase extraction identifies important terms within a given text.
AI-900 Practice Question: Describe features of Natural Language Processing workloads on Azure
This AI-900 practice question tests your understanding of describe features of natural language processing workloads on azure. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
What is 'key phrase extraction' in Azure AI Language?
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
Identifying the most important words and phrases that best represent a text's main topics
Key phrase extraction in Azure AI Language uses natural language processing to identify the most salient words and phrases that summarize the main topics of a text. It analyzes the document's structure and semantics to return a ranked list of key phrases, enabling quick understanding of core content without reading the entire text.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Encrypting sensitive phrases in a document for secure storage
Why it's wrong here
Encryption is a security operation — key phrase extraction identifies the most meaningful terms in text.
- ✓
Identifying the most important words and phrases that best represent a text's main topics
Why this is correct
Key phrase extraction surfaces the key concepts in text — enabling topic summarisation, tagging, and content understanding.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Finding and extracting password-like phrases from user messages for security monitoring
Why it's wrong here
Credential detection is a security feature — key phrase extraction identifies topically important terms, not sensitive data.
- ✗
Selecting the highest-scoring responses from a list of candidate answers
Why it's wrong here
Answer selection is question answering — key phrase extraction identifies important terms within a given text.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is confusing key phrase extraction with entity recognition or extractive question answering, as all three involve extracting text but serve fundamentally different purposes—key phrases summarize topics, entities identify specific named items, and QA retrieves direct answers to questions.
Trap categories for this question
Keyword trap
Encryption is a security operation — key phrase extraction identifies the most meaningful terms in text.
Detailed technical explanation
How to think about this question
Under the hood, Azure AI Language's key phrase extraction leverages transformer-based models (e.g., BERT) fine-tuned on large corpora to identify noun phrases and multi-word expressions that carry high semantic weight. The service returns a confidence score for each phrase, and the extraction is language-aware, supporting over 40 languages. In a real-world scenario, a customer support team could use key phrase extraction on thousands of tickets to automatically surface recurring issues like 'login failure' or 'payment gateway timeout' without manual review.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this AI-900 question test?
Describe features of Natural Language Processing workloads on Azure — This question tests Describe features of Natural Language Processing workloads on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Identifying the most important words and phrases that best represent a text's main topics — Key phrase extraction in Azure AI Language uses natural language processing to identify the most salient words and phrases that summarize the main topics of a text. It analyzes the document's structure and semantics to return a ranked list of key phrases, enabling quick understanding of core content without reading the entire text.
What should I do if I get this AI-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jun 11, 2026
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.
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