AI-102 Question 323
Single answerYou are designing a multi-turn conversational bot using Azure Bot Service and Language Understanding (LUIS). The bot needs to gather customer information such as name, email, and preferred contact time while allowing users to correct any input errors during the conversation. Which feature or approach should you implement to ensure the bot can handle corrections and maintain context across turns?
- A
Use dialog management in the Bot Framework SDK to track conversation state and prompt the user for specific information.
- B
Enable QnA Maker to handle multi-turn conversations and manage corrections automatically.
- C
Create an Azure Function to process and store user inputs outside of the conversation flow.
- D
Implement LUIS prebuilt entities to validate user inputs and automatically correct errors.
Show answer and explanation
Correct answer: A
Explanation
To create a multi-turn conversation, dialog management in the Bot Framework SDK is the most appropriate solution. It enables the bot to maintain context across multiple turns, prompt users for additional information, and handle corrections or changes in user input. Other options, such as QnA Maker or LUIS prebuilt entities, are not designed for managing the complexities of multi-turn dialogs.
- A. Correct.
Correct. Dialog management in the Bot Framework SDK allows you to track conversation context, manage prompts for user input, and handle user corrections effectively.
- B. Incorrect.
Incorrect. QnA Maker is primarily designed for single-turn question-answer scenarios and does not natively support complex multi-turn conversation flows or corrections.
- C. Incorrect.
Incorrect. While Azure Functions can process and store data, they do not inherently provide conversation state management or handle corrections in a multi-turn dialog.
- D. Incorrect.
Incorrect. LUIS prebuilt entities help with recognizing common data types but do not provide mechanisms for managing conversation context or handling user corrections.