Learn how to resolve chatbot response failures in Azure AI Language Service by leveraging alternate phrasing for QnA pairs. Enhance customer support efficiency with this essential guide.
Table of Contents
Question
Your organization, Xerigon Inc., is developing a chatbot for their e-commerce application using the question and answering capability of the Azure AI Language service. The chatbot is designed to assist customers by answering questions about their products and policies. You uploaded the document that contains information and questions on the electronic products.
One of the questions is, “What is the price of the product?”. During testing, it was observed that the chatbot failed to respond to the same question asked differently.
You are creating the QnA pair in the knowledge base. Which of the following options should you add while creating the QnA pair to resolve the issue?
A. Metadata
B. Chit-chat
C. Alternate phrasing
D. Follow-up prompts
Answer
C. Alternate phrasing
Explanation
You would add alternate phrasing while creating the QnA pair to resolve the issue. Alternate phrasing involves adding variations of the same question to the knowledge base, ensuring that the chatbot can recognize and respond accurately to differently worded user queries. For example, if the original question is, “What is the price of the product?”, alternate phrasing might include “How much does this product cost?” or “Can you tell me the product price?”. This helps improve the chatbot’s ability to match user queries with the correct answer.
You would not add metadata while creating the QnA pair to resolve the issue. Metadata is an optional setting and provides additional information to QnA pairs to help filter and customize responses. For example, you might use metadata to tag responses based on product categories or regional availability. Metadata is useful for categorization and filtering but does not solve the issue of varying question phrasing.
You would not add follow-up prompts while creating the QnA pair to resolve the issue. Follow-up prompts guide the user to ask related questions, creating a multi-turn conversation. For instance, if a user asks about a product’s price, the chatbot might prompt, “Would you like to know about discounts?”. This feature enhances user engagement and helps clarify the conversation but does not address the problem of responding to differently phrased queries.
You would not add chit-chat while creating the QnA pair to resolve the issue. Chit-chat functionality allows the chatbot to handle casual, non-business-related queries, such as “How are you?” or “Tell me a joke.”. It improves the conversational abilities of the chatbot but is unrelated to handling different phrasings of the same business-related query.
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