AI0-001 AI Concepts and Techniques Practice Question
An AI practitioner needs to extract key phrases from a large collection of customer support emails for trend analysis. Which technique is MOST suitable?
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
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Named entity recognition (NER)
Named entity recognition (NER) is the most suitable technique because it automatically identifies and extracts predefined entities such as names, dates, product names, and other key phrases from text. This directly supports extracting key phrases from customer support emails for trend analysis. Other techniques like language translation, text classification, and sentiment analysis do not focus on extracting specific phrases.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Named entity recognition (NER)
Why this is correct
NER extracts specific entities (e.g., product names, problems) which can serve as key phrases for trend analysis.
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Language translation
Why it's wrong here
Translation changes language but does not extract phrases.
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Text classification
Why it's wrong here
Text classification assigns categories but does not extract phrases.
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Sentiment analysis
Why it's wrong here
Sentiment analysis determines emotional tone, not key phrases.
About these practice questions
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.