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Training the email bot to understand topics

1 Task

15 mins

Visible to: All users
Beginner Pega Platform 8.8 Email English


U+ Bank wants to use Pega Email Bot to respond to customer problems and speed up business processes seamlessly. As a system architect, you are tasked to help train the already built email bot by adding training records to interpret emails and detect the correct information, such as topics and entities.

Use the following credentials to log in to the exercise system:

Role User name Password
System Architect EmailBotAuthor install12345!
Caution: To reuse the exercise system from a previous challenge, first complete the Creating a Pega Email Bot challenge. Otherwise, click Initialize Pega or Reset Instance in this challenge.

Your assignment consists of the following task:

Task: Train the email bot to understand topics

In the Training data tab of the email bot, click Add records to help train the email bot by adding training records to interpret emails.


You must initiate your own Pega instance to complete this Challenge.

Initialization may take up to 5 minutes so please be patient.

Challenge Walkthrough

Detailed Tasks

1 Train the email bot to understand topics

  1. Log in to App Studio as the System Architect with user name EmailBotAuthor using password install12345!.
  2. In the navigation pane of App Studio, click Channels.
  3. Click My Email Bot to access the channel.
    CH35681-1-EN-My Email Bot
  4. Click the Training data tab of the email bot.
  5. Click Add records to add the training records.
  6. Download the following file to upload the pre-classified set of training data:
  7. From Topic list, select the Address Change case.
  8. From the training data file, copy and paste the records related to the address and paste it in the message area and then Click Create record.
    CH35681-1-EN-Create a new training record

    Once the training data record is added, you can see the classification details in the right pane.
    In the NLP analysis section, the Language model, Topic, and any entities present are displayed on the bottom tile. The training data text is displayed in the upper tile, where any entities detected are highlighted.
    CH35681-1-EN-Review training data
  9. Repeat the steps 7-8 for the remaining three address records.
  10. Once the Address Change data entry is complete, repeat steps 7-9 for all the Complaint case records.
    CH35681-1-EN-new training record complaint
    CH35681-1-EN-review training data complaint
  11. Click Close.
  12. Under the Language list, select the check box to select all the records.
  13. Click Mark reviewed to add the records to the queue.
    CH35681-1-EN-Training data
  14. To the right of Add records, click the More icon, and then select Build Model to rebuild the natural language processing (NLP) model.
    CH35681-1-EN-Build model

    If the model build is successful, a message that shows the new F-Score is displayed at the top.
    CH35681-1-EN-success status
  15. Click Save.

Available in the following mission:

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