You create an automated Power Automate flow. The flow monitors incoming emails. Based on the email content, it redirects them to the appropriate departments, like sales, finance, or management. When an email comes with a management report, flow creates a report summary, puts it as the new email content, and sends this email to the management team with the attached original email. 
Please select two AI builder models that you should use for your flow.

Answer options:

A.Entity Extraction
B.Text recognition
C.Key Phrase Extraction
D.Sentiment Analysis
E.Category Classification

Correct Answers: C and E 
AI Builder provides several prebuilt Machine Learning cognitive models that users can use in their Power Platform products. AI Builder model list includes models like prediction, object detection, form processor, text classification, category classification, entity extraction, etc. If your business needs do not match the out-of-box models, you can train your models based on your data. 
In this task, we need to use the Category classification model to determine an email destination and forward an email to the appropriate department. If the Category classification model detects that email is for the management and contains a report, the flow should use the Key Phrase extraction model to create a report summary. Option C is correct because the Key Phrase Extraction model analyzes the text and extracts the most important phrases. This model creates the text summaries.
Option E is correct because the Category classification model analyzes an email text, determines the text language, and classifies text according to the predefined or trained categories.
Option A is incorrect because the Entity extraction model analyzes an email text, determines the text language, and extracts specific entities defined in a model. The standard model includes 28 such entities, like email address, date-time, phone number, etc. You can add other entities by training your model. But Entity extraction model does not extract key phrases from a report or provide a category classification of an email text.
Option B is incorrect because the Text recognition model extracts text from the images with printed or handwritten text. But this model does not extract key phrases from a report or provide a category classification of an email text.
Option D is incorrect because the Sentiment Analysis model analyses text on positive, negative, or neutral sentiment. But this model does not extract key phrases from a report or provide a category classification of an email text.
For more information about AI Builder models, please visit the below URLs: 

https://docs.microsoft.com/en-us/ai-builder/use-in-flow-overview
https://docs.microsoft.com/en-us/ai-builder/prebuilt-category-classification-pwr-automate
https://docs.microsoft.com/en-us/ai-builder/flow-key-phrase-extraction