- A
Use the prebuilt extractive summarization API in Azure AI Language for both languages, specifying the maximum summary length.
The prebuilt extractive summarization API supports English and Spanish, and allows configuring summary length. It requires no custom model training.
- B
Train a custom extractive summarization model using Azure AI Language's custom text summarization feature with labeled data in both languages.
Why wrong: Custom extractive summarization requires labeled data and training, which is more effort than using the prebuilt API, especially since the prebuilt model already supports the required languages.
- C
Use the conversation summarization API to summarize each article.
Why wrong: Conversation summarization is optimized for dialogues, not news articles; it may not produce good results.
- D
Use the prebuilt abstractive summarization API to generate summaries.
Why wrong: Abstractive summarization generates new sentences that may not be directly extracted from the article, which violates the requirement for extractive summaries.
Quick Answer
The correct choice is to use the prebuilt extractive summarization API in Azure AI Language for both languages, specifying the maximum summary length. This approach works because extractive summarization is a prebuilt, no-code capability that selects the most salient sentences directly from the source text, making it ideal for generating concise, fact-based summaries under 100 words without requiring custom model training. Azure AI Language natively supports both English and Spanish for this feature, so you can process your bilingual news corpus with a single API call. On the AI-102 exam, this question tests your ability to distinguish between prebuilt and custom language features, with a common trap being the assumption that extractive summarization requires a custom model—it does not. Remember that extractive summarization pulls existing sentences, while abstractive generates new ones; for news articles needing verbatim accuracy, extractive is the safer bet. A useful memory tip: “Extractive extracts, abstractive invents.”
AI-102 Practice Question: Implement natural language processing solutions
This AI-102 practice question tests your understanding of implement natural language processing solutions. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
Your organization runs a popular news website. You want to use Azure AI Language to automatically generate summaries of news articles for the homepage. The summaries must be concise (under 100 words), extractive (selecting key sentences from the article), and available in both English and Spanish. You have a large corpus of articles in both languages. You need to implement a solution that requires minimal custom development and leverages Azure AI Language's prebuilt capabilities. Which approach should you take?
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
Use the prebuilt extractive summarization API in Azure AI Language for both languages, specifying the maximum summary length.
Option A is correct because Azure AI Language's prebuilt extractive summarization supports multiple languages, including English and Spanish, and can be configured to output concise summaries. Option B is wrong because extractive summarization is a prebuilt feature, not a custom model. Option C is wrong because abstractive summarization generates new sentences, not extractive. Option D is wrong because conversational summarization is designed for multi-turn conversations, not news articles.
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.
- ✓
Use the prebuilt extractive summarization API in Azure AI Language for both languages, specifying the maximum summary length.
Why this is correct
The prebuilt extractive summarization API supports English and Spanish, and allows configuring summary length. It requires no custom model training.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Train a custom extractive summarization model using Azure AI Language's custom text summarization feature with labeled data in both languages.
Why it's wrong here
Custom extractive summarization requires labeled data and training, which is more effort than using the prebuilt API, especially since the prebuilt model already supports the required languages.
- ✗
Use the conversation summarization API to summarize each article.
Why it's wrong here
Conversation summarization is optimized for dialogues, not news articles; it may not produce good results.
- ✗
Use the prebuilt abstractive summarization API to generate summaries.
Why it's wrong here
Abstractive summarization generates new sentences that may not be directly extracted from the article, which violates the requirement for extractive summaries.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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Implement natural language processing solutions — study guide chapter
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FAQ
Questions learners often ask
What does this AI-102 question test?
Implement natural language processing solutions — This question tests Implement natural language processing solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use the prebuilt extractive summarization API in Azure AI Language for both languages, specifying the maximum summary length. — Option A is correct because Azure AI Language's prebuilt extractive summarization supports multiple languages, including English and Spanish, and can be configured to output concise summaries. Option B is wrong because extractive summarization is a prebuilt feature, not a custom model. Option C is wrong because abstractive summarization generates new sentences, not extractive. Option D is wrong because conversational summarization is designed for multi-turn conversations, not news articles.
What should I do if I get this AI-102 question wrong?
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
1 more ways 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. You need to summarize a large document using Azure AI Language. Which feature should you use?
easy- ✓ A.Document summarization
- B.Key phrase extraction
- C.Entity recognition
- D.Sentiment analysis
Why A: Option B is correct because Document summarization (extractive or abstractive) is designed to summarize documents. Option A is wrong because Key phrase extraction extracts phrases, not summaries. Option C is wrong because Entity recognition identifies entities. Option D is wrong because Sentiment analysis gives sentiment scores.
Last reviewed: Jun 20, 2026
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.
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