Matching patterns and getting their values in Watson Assistant/Conversation

When IBM Watson Assistant (formerly known as Watson Conversation) is deciding how to respond to a user's utterance it is vital that it correctly identifies the intent (what the user wants to do) and the entities (what are the things involved in the intent). For example, if the user says "I want to buy a book" - the intent would be #MakePurchase and the entity @ItemOfInterest would have a value of "book".

In earlier releases of Watson Assistant, the only way to specify possible entity values was either by manually specifying a list of possible values or else by selecting one of the predefined system entities such as @sys-date. Sometimes this works quite well, but other times (e.g. when you are expecting an email address or an account number) is not feasible to list all of the possible values that people might enter.

Luckily, the latest version of the Watson Assistant service allows you to specify allowable entity values with a regular expression. Unfortunately, people sometimes find it hard to retrieve the matched value from a pattern match. If you are not careful you will be told that an email address was specified and not what exact email address was given. Therefore this blog post works through a very simple conversational design to explain what you need to do.

First off, you define an intent. We will call our intent #sendMessage and we give Watson a few examples of what the user might say when they want to send a message.

Then we create a @contact_info entity which we expect users to specify when they are sending a message. To complete this entity, the user types a message indicating that they want to send a message. We expect that the message will also contain details of where to send the message, either an email address or a phone number (the phone number can be specified in US style or in the e164 standard common in other parts of the world).

This picture shows how the entity definition will look. Don't worry if you can't read the regular expressions in the screenshots, you can download the workspace design.

Now you need to insert a dialog node to handle requests to send messages. We create a node in our dialog flow which is triggered when Watson detects that the user's intention is to send a message. We know that it is necessary to have contact information to send a message, so if the user didn't supply this we will prompt them.

Then we need sub-nodes which deal with sending either emails or phone messages. We select which to activate depending the value of the @contact_info variable, which will be either email, us_phone_num or e164_phone_num.

When sending a message, it is not enough to know that the user gave us an email address - we need to know the exact email address given.  To do that, we  need to define a variable whose value will be specified as  "<? @contact_info.literal ?>".  The screen shot below shows the dialog node for sending a phone message.

This is the end of our very simple BOT. If you want to see this in action, download the design file here and  import it into your own Watson Assistant instance. Here is a screenshot of what I saw when I clicked on the "Try it out" button to see the bot in action.

In summary, regular expression entities can be really useful, so long as you remember to use the @entity_name.literal syntax to get the actual content that was matched rather than simply which rule was fire.