Heads up! To view this whole video, sign in with your Courses account or enroll in your free 7-day trial. Sign In Enroll

Build a Chatbot with Watson APIs

Preview

Start a free Courses trial
to watch this video

Sign up for Treehouse

Intents, Entities, and Dialogs

3:30 with Ben Jakuben

We are now going to zero in on the important things you need to know to build a chatbot using the Conversation Service: Intents, Entities, and Dialogs. Let's take a look at what they are and how they fit together.

Definitions

  • Intent: An intent represents the purpose of a user's input. You define an intent for each type of user request you want your application to support.
  • Entity: An entity represents a term or object that is relevant to your intents and that provides a specific context for an intent. You list the possible values for each entity and synonyms that users might enter.
  • Dialog: A dialog is a branching conversation flow that defines responses to the defined intents and entities. You use the dialog builder in the tool to create conversations with users to provide responses.

For more information, check out Configuring a Conversation workspace in the docs.

Related Discussions

Have questions about this video? Start a discussion with the community and Treehouse staff.

Sign up

    Related Discussions

    Have questions about this video? Start a discussion with the community and Treehouse staff.

    Sign up

    [MUSIC] Welcome back we're now going to zero in on 0:00
    the important things that you need to know to build a chat bot using 0:03
    the conversation service that we created earlier. 0:08
    >> The first thing we should do is get a bird's eye view of what we're building and 0:12
    what the overall ecosystem Looks like. 0:18
    We have provided you with a sample web app that will be the client in this. 0:21
    The web app is using some Watson SDKs to make it very easy to communicate with 0:26
    the Watson APIs available along the Watson Developer Cloud over here. 0:31
    Users will input text into our simplified app, but 0:36
    not that Watson can process text, voice, and visual input. 0:41
    Our app will first pass the input data To a new conversation service that we create. 0:47
    Each time we use a service from Watson, we create our own instance to connect to. 0:53
    That allows us to train our unique instance with our own custom data. 0:59
    The conversation service processes the input using its underlying 1:03
    natural language processing technology. 1:08
    Later we'll see how to communicate with more than just one service. 1:11
    As we go along and build this part, 1:16
    it will help to think about how it fits into this overall picture. 1:19
    Then, now seems like a good time to point out that IBM has a variety of And 1:24
    s available to make it easy for you to get started on a new p[roject. 1:30
    No matter what you are working on, the are available 1:36
    on and helpful are available on this page. 1:41
    Both of these links are available for you in the teahers notes. 1:46
    Back in our diagram, let's zoom into the conversation service. 1:51
    Like a regular conversation, a conversation service with Watson has 1:56
    some key elements in the speech or text that are needed for understanding. 2:01
    The Watson conversation service defined these parts as intents, 2:07
    entities, and dialog. 2:12
    And they work together to deliver a conversational response to the user. 2:14
    An intent represents the purpose of a user's input. 2:19
    You define an intent for each type of user request you want your application to 2:23
    support In the tool the name of an intent is always prefixed the pound character. 2:29
    To train the workspace to recognize your intents you supply lots 2:35
    of examples of user input and indicate which intents they left. 2:40
    >> An entity represents a term or object that is relevant to your intents And 2:45
    that provides a specific context for an intent. 2:51
    For example, an entity might represent a city where the user wants to find 2:54
    a business location or the amount of the bill payment. 2:58
    In the tool the name of an entity is always prefix with the @ character. 3:01
    To train the workspace to recognize your entities you list the possible values for 3:04
    each entity and synonyms that users might enter. 3:09
    >> A dialog is a brancing converstaion flow that defines 3:12
    responses to the defined intents and entities. 3:17
    You use the dialog building inthe tool to create 3:21
    conversations with users to provide responses. 3:26

    You need to sign up for Treehouse in order to download course files.

    Sign up

      You need to sign up for Treehouse in order to set up Workspace

      Sign up