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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.
Links
- Watson Developer Cloud on GitHub
- Watson Starter Kits - These contain starter app code for common use cases.
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.
[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
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