Microsoft Azure AI Fundamentals AI-900 Practice Question
An insurance company wants to automatically extract names of people, locations, and organizations from a large set of claim documents to facilitate data analysis.
Which natural language processing (NLP) technique is most appropriate for this task?
Entity recognition is used to identify and classify key elements in text into predefined categories such as names of people, locations and organizations. This makes it suitable for extracting such specific information from large text datasets.
Key Phrase Extraction identifies important phrases but does not categorize them into entities.
Sentiment Analysis determines the emotional tone of text.
Text Summarization condenses text to key points but doesn't extract specific entities.
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How is Key Phrase Extraction different from Entity Recognition?
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Microsoft Azure AI Fundamentals AI-900
Describe Features of Natural Language Processing (NLP) Workloads on Azure
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