Learn how Azure AI Language simplifies key phrase extraction by analyzing unstructured text to identify main concepts. Discover its applications and how to get started efficiently.
Table of Contents
Question
Which of the following actions should you take when you want to use key phrase extraction on Azure AI Language?
A. Create a custom AI model for extracting entity categories.
B. Submit raw unstructured data for analysis.
C. Identify and categorize PII data.
D. Mine the data for clues about negative or positive sentiment.
Answer
B. Submit raw unstructured data for analysis.
Explanation
The correct action to take when you want to use key phrase extraction on Azure AI Language is to submit raw unstructured data for analysis. Key phrase extraction requires providing raw, unstructured text data without pre-processing or formatting. Azure AI Language analyzes the text and identifies the most significant terms and phrases.
Mining the data for clues about negative or positive sentiment is a task that falls under the domain of sentiment analysis, not key phrase extraction.
To identify and categorize PII data involves personally identifiable information (PII) detection, which is a separate function altogether and not related to key phrase extraction.
Creating a custom AI model for extracting entity categories is a task that describes custom entity recognition which focuses on specific entities such as locations and companies, not general key phrases.
Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.