Creating training data manually for an email bot

To ensure that Pega Email Bot interprets emails in the correct way, manually create training records in the system. Training records provide valuable information for the email bot that strengthens the artificial intelligence algorithms and improves the accuracy of your text analytics model. By training the model, you ensure that the email bot detects the correct topics, entities, and language. For example, you can add a training record that specifies a request for an insurance quote for a 1968 Ford Mustang GT. If you connect that record to a car insurance topic, the system learns to associate this information with a car insurance case.
Before you begin: Enable the recording of training data to gather training records when the system receives emails from users. For more information, see Enabling the training data recording for an email bot.
You review the training data before applying the changes to the text analytics model.
  1. In the header of Dev Studio, click the name of the application, and then click Channels and interfaces.
  2. In the Current channel interfaces section, click the icon that represents your existing Email channel.
  3. On the Email channel configuration page, click the Training data tab.
  4. In the toolbar, click Add records.
  5. If you configure multiple languages for the email bot, in the Creating new training record window, in the Language list, select the language for the training record, for example, English.
  6. In the Topic field, press the Down arrow key, and then select a name of a topic to which the training record relates, for example, Car insurance.
  7. In the field area below the Topic field, enter the text for the training record.
    The text must be a good representation of sample user input from which the email bot can learn to respond to emails.
    For example: Hi, I would like to obtain a car insurance quote for my 1968 Ford Mustang GT. Thank you for your help, Andrew.
  8. Click Create record.
    Result: The system displays the training record in the list on the Training data tab. The Review training data section displays the training record contents with the detected entities highlighted. The NLP analysis section displays the detected language, topic, and entity types that are used in the training data.
  9. Optional: To add more training records for the email bot, repeat steps 4 through 8.
  10. Click Save.
What to do next: Train the email bot by building a text analytics model. For more information, see Applying changes to a text analytics model for an email bot.