Creating entities for an email bot

To ensure that Pega Email Bot detects the correct information in emails, such as a location, date, or postal code, update the training data in the system by adding new entities. For example, if you want to detect the make of cars in emails, you can create the CarMake entity. At run time, your email bot can use this detected information to provide a right response to an email.
Before you begin: Enable the recording of training data. For more information, see Enabling the training data recording for an email bot.
The email bot can also use an entity for other purposes. The system can automatically copy phrase from a detected entity, for example, Ford, to a property of a related business case. For more information, see Setting up entity property mapping.
  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. Optional: If you configure multiple languages for the email bot, to filter data records by a language, in the Language list, select a language.
    For example: To display data records only detected in the Italian language, select Italian.
  5. In the list of training records, select a data record.
    Result: The Review training data pane displays the detected entities and the NLP analysis section displays the entity types for the training data record.
  6. In the Review training data section, in the data record content, highlight and right-click the text that you want to map to the new entity, and then click New entity.
    For example: To select a car make in the text, highlight the word Ford.
  7. In the Create new entity window, in the Entity name field, enter a name for the entity, and then click Submit.
    For example: To create an entity for a car make, enter Car Make.
  8. Optional: To create more entities for the data record, repeat steps 4 through 7.
  9. Optional: To use this training record to improve the artificial intelligence algorithm of your email bot, in the Review training data section, click Mark reviewed.
    Create at least 15 records in the training sample so that the system learns how to detect the right information in emails.
  10. Click Save.
What to do next: Teach the email bot the reviewed and corrected training records by rebuilding the text analytics model. For more information, see Applying changes to a text analytics model for an email bot.