Visualization of training dialogs for a conversational bot

A system comprising:

• a processor;
• and
• a storage memory storing computer-readable instructions, which when executed by the processor, cause the processor to:
• access data associated with training dialogs that represent interactions with a chatbot, the training dialogs employed to train a machine learning model used by the chatbot;
• identify first decisions of the chatbot that are based at least on declarative rules and second decisions of the chatbot that are based at least on machine learning by the machine learning model used by the chatbot;
• and
• present the first decisions and the second decisions in a tree form where the first decisions are presented in the tree form differently from the second decisions.

A method comprising:

• accessing data associated with training dialogs that represent interactions with a chatbot, the training dialogs employed to train a machine learning model used by the chatbot;
• identifying first decisions of the chatbot that are based at least on declarative rules and second decisions of the chatbot that are based at least on machine learning by the machine learning model used by the chatbot;
• and
• presenting the first decisions and the second decisions in a graph form where the first decisions are presented in the graph form differently from the second decisions.

A method comprising:

• accessing data associated with training dialogs that represent interactions with a chatbot;
• presenting conversational rounds of the chatbot in a graph form, the conversational rounds being based on one or more of declarative rules, programmatic coding, or machine learning by the chatbot;
• receiving input dragging a particular round of the chatbot from a first branch of the graph form to a second branch of the graph form;
• and
• updating the training dialogs based at least on the dragging of the particular round of the chatbot from the first branch of the graph form to the second branch of the graph form.