Table of Contents

Editing data records

When you enable the recording of training data and Pega Email Bot receives emails, the system saves the content of each email as a training data record. You can then edit this training data before it is added to the model, to remove irrelevant content and fix grammatical or formatting errors in the record. This ensures that your training data is of high quality, so that the text analytics model is only trained using the most relevant, correct topics, entities, and language.

Enable recording of training data. For more information, see Enabling the training data recording for an email bot.
  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. In the Email channel, 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.

    To display data records only detected in the German language, select German.
  5. In the list of training records, select a data record.

    The Review training data section displays the detected entities, and the NLP analysis section displays the detected language, topic, and entity types for the training data record.
  6. In the Review training data pane, click the More icon, and then click Edit.

  7. In the Update text window, edit the text for the training record, and then click OK.

  8. Optional:

    To use this training record to improve the artificial intelligence of the email bot, in the Review training data section, click Mark reviewed.

  9. Optional:

    To edit additional records for the email bot, repeat steps 4 through 8.

  10. Click Save.

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.

  • Correcting identified topics

    If you want to ensure that Pega Email Bot is accurately detecting the topic and intent of the emails it receives, you can review and correct the topics in the training data records. You train the system by correcting the identified topics in each training record, and then rebuilding the text analytics model with the updated information. This improves the accuracy of the cases and responses that the email bot suggests when it detects the relevant topic.

  • Correcting identified languages

    To train Pega Email Bot to detect the correct language in emails, select the language for a training record, and then build a text analytics model for the system. Correcting the detected language in training data ensures that the email bot selects the right languages to perform text analysis of emails.

  • 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.

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