Create an open-ended entity
Use an open-ended entity when you want to improve intent prediction accuracy. Open-ended entities help your model focus on the context of the utterances.
Before you begin
- Make sure that the NLU Workbench plugin, NLU Workbench - Core plugin, NLU Common Model plugin, and Predictive Intelligence plugin are all installed and activated on your instance.
- Create or use an existing NLU model for Virtual Agent or AI Search.
- Create or use an existing intent.
- Role required: nlu_editor, nlu_admin, or admin. The nlu_editor must be assigned to the model.
About this task
Open-ended entities tell the model to focus on the context of the entity rather than the entity itself. When you mark a word or phrase as open-ended, the system skips the entity and predicts the intent from the context that precedes or follows the entity in the utterance.
For example, in the utterance I want to order an iPhone, you annotate the words "an iPhone" as an open-ended entity. The model focuses on the context, predicting the user wants to order something. Since there are numerous things the user could want to order, naming all of them would be an unbearable task for the model author.
Using an open-ended entity instead of a simple entity helps the model focus on the rest of the utterance and not the entity. In the iPhone example, the entity itself is less relevant; so you want the system to ignore it.
For this example scenario, you've created an NLU model with an intent for your users to order company merchandise.
Procedure
What to do next
Train your model to save the entities. You can try your model to see if it interprets the utterance based on the context of the entity, rather than the entity itself.
- Select Try Model.
- Enter I want to order a polo.
- Select Go.
The model predicts the intent and shows that it used the merch entity for the a polo value.