Discover the capabilities of entity recognition in natural language processing. Explore how this technology extracts and categorizes key entities from text, enabling deeper insights and enhanced information management.
Table of Contents
Question
You use natural language processing to process text from a Microsoft news story. You receive the output shown in the following exhibit.
Which type of natural languages processing was performed?
A. entity recognition
B. key phrase extraction
C. sentiment analysis
D. translation
Answer
B. key phrase extraction
Explanation
Key phrase extraction/ Broad entity extraction: Identify important concepts in text, including key phrases and named entities such as people, places, and organizations.
You can provide the Text Analytics service with unstructured text and it will return a list of entities in the text that it recognizes. You can provide the Text Analytics service with unstructured text and it will return a list of entities in the text that it recognizes. The service can also provide links to more information about that entity on the web. An entity is essentially an item of a particular type or a category; and in some cases, subtype, such as those as shown in the following table.
Reference
Microsoft Learn > Azure > Cognitive Services > Language Service > What is Azure Cognitive Service for Language?
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