An intent identifies an intended action of your intended users. For example, an utterance or query spoken by a user could express an intent to order a drink. As you develop an NLU model, you define intents based on what you want your users to be able to do in your application. A trained NLU model lets you correctly interpret a user’s intent from their words. You can then link intents to functions or methods in your client application logic to fulfill the user’s intent.

Here are some examples of intents you might define:

  • ORDER_COFFEE: For example, if a user said “I’d like an iced vanilla latte.”
  • GET_INFO: For example, if a user asked “What’s in the espresso macchiato?”
  • CANCEL_ORDER: For example, if a user remarked “I’ve changed my mind, cancel that.”

Intents are usually associated with entities to further specify particulars about the intended action.