Drag and Drop Question Match the types of natural language processing workloads to the appropriate scenarios. To answer, drag the appropriate workload type from the column on the left to its scenario

The correct answer is Entity recognition; Sentiment analysis; Translation. The three correct matches align NLP workload types to their most appropriate real-world scenarios: Entity Recognition identifies and classifies named entities (people, places, organizations, dates) within text; Sentiment Analysis evaluates the emotional tone or opinion expressed

Submitted by tom_us· Mar 30, 2026Describe features of Natural Language Processing (NLP) workloads on Azure - typically part of the 'Describe features of Natural Language Processing workloads' domain in AI-900 (Azure AI Fundamentals) or similar AI certification exams.

Question

Drag and Drop Question Match the types of natural language processing workloads to the appropriate scenarios. To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all. NOTE: Each correct match is worth one point. Answer:

Exhibit

Answer Area

Drag items

Entity recognitionKey phrase extractionLanguage modelingSentiment analysisSpeech recognition and speech synthesisTranslation

Correct arrangement

Entity recognition
Sentiment analysis
Translation

Explanation

The three correct matches align NLP workload types to their most appropriate real-world scenarios: Entity Recognition identifies and classifies named entities (people, places, organizations, dates) within text; Sentiment Analysis evaluates the emotional tone or opinion expressed in text (positive, negative, neutral); and Translation converts text or speech from one language to another. These are distinct, well-defined NLP tasks each with a specific purpose that maps directly to its scenario description.

Topics

#Natural Language Processing#NLP Workloads#AI Services#Azure Cognitive Services

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