How to model classical NLU intents and entities(slots)?

The calendar example's actions are similar to intents that one would define for Dialogflow or Alexa. How to use OpenAI as an intent NLU engine?

The issue is that "yes" and "yes, please" matches the YesIntent but "ok" or other affirmative responses do not.

Inputs:

• yes
• ok
• sure
• i will
• yes, please

Type schema:

// The following types define the structure of an object of type BotIntent that represents a user request that matches most closely to the sample or synonyms

export type BotIntent = YesIntent | NoIntent | UnknownIntent;

// if the user types text that closely matches 'yes' or a synonym, this intent is used
export type YesIntent = {
  intentName: 'YesIntent';
  sample: 'yes';
  text: string;
};

// if the user types text that closely matches 'no' or a synonym, this intent is used
export type NoIntent = {
  intentName: 'NoIntent';
  sample: 'no';
  text: string;
};

// if the user types text that can not easily be understood as a bot intent, this intent is used
export interface UnknownIntent {
  intentName: 'UnknownIntent';
  sample: 'unknown';
  // text typed by the user that the system did not understand
  text: string;
}

How to model more complicated intents with required and optional entities?

Start with the calendar example and the BotIntent, YesIntent, NoIntent, and UnknownIntent schema shown in the issue. Investigate how the project currently handles affirmative variants and more complicated intents with required or optional entities; done should be a documented or implemented approach that covers the listed inputs and entity cases.