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AI-900 · Question #89

Drag and Drop Question You plan to apply Text Analytics API features to a technical support ticketing system. Match the Text Analytics API features to the appropriate natural language processing…

The correct answer is Sentiment analysis; Key phrase extraction; Entity recognition. Sentiment analysis is correct for determining customer satisfaction or frustration levels from ticket text (e.g., identifying negative tone in complaints). Key phrase extraction identifies the most important topics or issues within a support ticket (e.g., extracting 'login…

Submitted by layla.eg· Mar 30, 2026Describe features of natural language processing (NLP) workloads on Azure - specifically matching Azure Text Analytics API capabilities (sentiment analysis, key phrase extraction, entity recognition, language detection) to real-world business scenarios, as tested in the Microsoft Azure AI Fundamentals (AI-900) certification.

Question

Drag and Drop Question You plan to apply Text Analytics API features to a technical support ticketing system. Match the Text Analytics API features to the appropriate natural language processing scenarios. To answer, drag the appropriate feature from the column on the left to its scenario on the right. Each feature may be used once, more than once, or not at all. NOTE: Each correct selection is worth one point. Answer:

Exhibit

AI-900 question #89 exhibit

Answer Area

Drag items

entity recognitionKey phrase extractionLanguage detectionSentiment analysis

Correct arrangement

  • Sentiment analysis
  • Key phrase extraction
  • Entity recognition

Explanation

Sentiment analysis is correct for determining customer satisfaction or frustration levels from ticket text (e.g., identifying negative tone in complaints). Key phrase extraction identifies the most important topics or issues within a support ticket (e.g., extracting 'login failure' or 'network error' as key themes). Entity recognition detects and categorizes specific named entities such as product names, software versions, error codes, or customer account references within ticket content, enabling structured data extraction from unstructured text.

Topics

#Text Analytics API#Natural Language Processing#Azure Cognitive Services#AI-900 Language Features

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