Correcting training data in an email bot

When you want to improve the ability of Pega Email Bot to detect topics, language, and entities, you can review and correct the training data in the system. By correcting the training data and rebuilding the text analytics model, you improve the artificial intelligence of the email bot and teach it to more accurately detect the desired information in emails. The system can then suggest the right business case or email response, based on the detected information. For example, an email bot detects a request for a car insurance quote in an email by identifying the relevant topic and entities. The email bot can then create a business case for a car insurance quote and send an automatic reply.

Before you begin: Enable recording of training data. For more information, see Enabling the training data recording for an email bot.

When you enable the recording of training data and the email bot receives an email, the system saves the email as a training record. (You can also manually create a training record that contains sample information for an email from a user). Once you correct the data detected in the training record, you mark the record as reviewed. The system then uses the reviewed training data to rebuild the improved text analytics model.

Procedure

Add new entities to a training record.
For more information, see Creating entities for an email bot.
Modify text in a training record.
For more information, see Editing data records.
Update existing entities in a training record.
For more information, see Correcting existing entities.
Update the language to be detected in a training record.
For more information, see Correcting identified languages.
Update the topic to be detected in a training record.
For more information, see Correcting identified topics.

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.