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Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have a chatbot that uses question answering in Azure Cognitive Service for Language Users report that the responses of the chatbot lark formality when answering spurious questions You need to ensure that the chatbot provides formal responses to spurious questions. Solution: From Language Studio, you change the chitchat source to qna_chitchit_friindly.tsv. and then retrain and republish the model. Does this meet the goal?
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have a chatbot that uses question answering in Azure Cognitive Service for Language Users report that the responses of the chatbot lack formality when answering spurious questions You need to ensure that the chatbot provides formal responses to spurious questions. Solution: From Language Studio, you change the chitchat source to qna_chitchat_professional.tsv. and then retrain and republish the model. Does this meet the goal?

Question 103 - AI-102 discussion

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You are developing the chatbot.

You create the following components:

A QnA Maker resource

A chatbot by using the Azure Bot Framework SDK

You need to integrate the components to meet the chatbot requirements.

Which property should you use?

A.
QnAMakerOptions.StrictFilters
Answers
A.
QnAMakerOptions.StrictFilters
B.
QnADialogResponseOptions.CardNoMatchText
Answers
B.
QnADialogResponseOptions.CardNoMatchText
C.
QnAMakerOptions.RankerType
Answers
C.
QnAMakerOptions.RankerType
D.
QnAMakerOptions.ScoreThreshold
Answers
D.
QnAMakerOptions.ScoreThreshold
Suggested answer: C

Explanation:

Scenario: When the response confidence score is low, ensure that the chatbot can provide other response options to the customers. When no good match is found by the ranker, the confidence score of 0.0 or "None" is returned and the default response is "No good match found in the KB". You can override this default response in the bot or application code calling the endpoint.

Alternately, you can also set the override response in Azure and this changes the default for all knowledge bases deployed in a particular QnA Maker service.

Choosing Ranker type: By default, QnA Maker searches through questions and answers. If you want to search through questions only, to generate an answer, use the RankerType=QuestionOnly in the POST body of the GenerateAnswer request.

Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/concepts/best-practices

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asked 26/09/2024
Feroz Khan
43 questions
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