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AZ-204 · Question #65

Drag and Drop Question You develop a bot by using Language Understanding Intelligence Service (LUIS) and the .NET Bot framework. You use LUIS in the Azure portal to optimize the bot. You review the…

The correct answer is Create an intent for each event type.; Add example utterances.; Create a List entity. The correct sequence begins with creating an intent for each event type, which allows LUIS to categorize user goals (e.g., 'GetTimeInfo', 'GetVenueInfo'). Next, adding example utterances trains the model by providing representative samples of how users phrase these requests…

Submitted by suresh_in· Mar 30, 2026Design and Implement Conversational AI Solutions - specifically configuring LUIS intents, utterances, and entities to improve prediction accuracy in Azure Bot Service applications

Question

Drag and Drop Question You develop a bot by using Language Understanding Intelligence Service (LUIS) and the .NET Bot framework. You use LUIS in the Azure portal to optimize the bot. You review the utterances and determine that users are requesting time and venue information for events. You need to improve the prediction efficiency of the bot. Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. NOTE: Each correct selection is worth one point. Answer:

Exhibit

AZ-204 question #65 exhibit

Answer Area

Drag items

Create an intent for each event type.Add a patternCreate a Pattern any entity.Add example utterances.Create a List entity.

Correct arrangement

  • Create an intent for each event type.
  • Add example utterances.
  • Create a List entity.

Explanation

The correct sequence begins with creating an intent for each event type, which allows LUIS to categorize user goals (e.g., 'GetTimeInfo', 'GetVenueInfo'). Next, adding example utterances trains the model by providing representative samples of how users phrase these requests. Finally, creating a List entity is appropriate here because event names and venues are typically finite, enumerable sets of values - a List entity captures these structured, predefined values (like specific event names or venues) to extract them accurately from utterances, directly improving prediction efficiency for time and venue queries.

Topics

#LUIS#Natural Language Processing#Bot Framework#Entity Types

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