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Verifying detected topics and entities

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To ensure that Pega Intelligent Virtual Assistant™ (IVA) responds correctly to user requests during a chat session, you can first simulate conversations with the chatbot and then verify the detected information in the preview console for a conversational channel. As a result, the system becomes more responsive and improves its text analysis and artificial intelligence.

For example, you can verify that the system correctly detects the topic related to car insurance, the subject matter, and detects a car model and make, when a user asks for a car insurance quote for their car in the chat session.
  1. In the navigation pane of App Studio, click Channels.

  2. In the Current channel interfaces section, click the icon that represents your existing Alexa, Digital Messaging, or Legacy Webchat channel.

  3. In the channel, click the Behavior tab.

  4. At the top of the preview console, turn on the Show analysis switch.

    When you enter sample text in the preview console, the analysis shows the topic detected and the system's confidence in the correctness of the detected topic, as a percentage.
  5. In the preview console in the right panel, type in a typical user phrase that starts a business case.

    To request a car insurance quote, enter: I would like to request a car insurance quote for my Ford Mustang GT.
    The preview console displays the detected topic below the text that you enter, and starts the associated business case in the chatbot.
  6. Correct the topic (subject matter) or entity detected in user input:

    Choices Actions
    If no topic was found
    1. Click Define topic below the entered text.

    2. In the Topic field, press the Down arrow key, and then select the correct topic.

    3. In the field below the topic name, enter a sample of user input to associate with the topic.

      Enter How can I get a car quote?
    4. Optional:

      To add additional sample phrases to associate with the topic, click Add example, and then in the field below, enter the text.

    5. Click Submit.

    If the wrong topic was found
    1. Click the topic name located below the entered text.

    2. In the Topic field, press the Down arrow key, and then select the correct topic.

    3. In the field below the topic name, enter a sample of user input to associate with the topic.

    4. Optional:

      To add additional sample phrases to associate with the topic, click Add example, and then in the field below, enter the text.

    5. Click Submit.

    If no entity was found
    1. In the text section below the detected sentiment, highlight and right-click the text that you want to map to the new entity.

    2. Click New entity.

      To select a car make in the text, highlight the word Ford.
    3. In the Create new entity window, in the Entity name field, enter a name for the entity, and then click Submit.

    If the wrong entity was found
    1. In the text section below the detected sentiment, highlight and right-click the text for an existing entity.

    2. Click the name of another entity.

      To ensure the car make in the text maps to the CarMake entity, highlight and right-click Ford, and then click #CarMake.
  7. Click the Like icon next to the topic name located below the entered text.

    Clicking this icon is important in the IVA training process, and improves the correct detection of topics.
  8. Click Save.

The following figure shows added entities in sample user input, in the preview console:
Two defined entities in text in the preview console
Car make and car model entities in user input in the preview console.
Ensure that the IVA learns from the corrected topics and validated entities by building the text analytics model. For more information, see Applying simulation changes to a text analytics model.
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