Discover three proven methods for generating question and answer text using QnA Maker. Explore how you can leverage existing webpages, employ automated machine learning, or manually input data to build a robust and informative chatbot.
Table of Contents
Question
You need to provide content for a business chatbot that will help answer simple user queries. What are three ways to create question and answer text by using QnA Maker?
Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. Generate the questions and answers from an existing webpage.
B. Use automated machine learning to train a model based on a file that contains the questions.
C. Manually enter the questions and answers.
D. Connect the bot to the Cortana channel and ask questions by using Cortana.
E. Import chit-chat content from a predefined data source.
Answer
A. Generate the questions and answers from an existing webpage.
C. Manually enter the questions and answers.
E. Import chit-chat content from a predefined data source.
Explanation
The correct answers are A. Generate the questions and answers from an existing webpage, C. Manually enter the questions and answers, and E. Import chit-chat content from a predefined data source.
QnA Maker is a cloud-based API service that creates a conversational, question-and-answer layer over your data. QnA Maker enables you to power a question-and-answer service from your semi-structured content like FAQ documents, URLs, and product manuals.
There are three ways to create question and answer text by using QnA Maker:
- Generate the questions and answers from an existing webpage: QnA Maker can automatically extract question-answer pairs from a webpage that contains FAQ content, such as a support website, a product manual, or a blog post. You can provide the URL of the webpage and QnA Maker will crawl the webpage and create a knowledge base with the extracted questions and answers.
- Manually enter the questions and answers: QnA Maker allows you to manually add, edit, or delete questions and answers in your knowledge base. You can use the QnA Maker portal or the REST APIs to create custom question-answer pairs that suit your specific needs.
- Import chit-chat content from a predefined data source: QnA Maker provides a set of prebuilt chit-chat datasets that contain common conversational phrases and responses, such as greetings, compliments, or jokes. You can import chit-chat content from a predefined data source and add personality to your chatbot. You can also customize the chit-chat content to match your chatbot’s tone and style.
The other two options are not ways to create question and answer text by using QnA Maker, but they can be used for other purposes:
- Use automated machine learning to train a model based on a file that contains the questions: This is not a QnA Maker feature, but a Custom Question Answering feature. Custom Question Answering is a cloud-based service that allows you to create and train custom question answering models with your own data. You can use automated machine learning to train a model based on a file that contains the questions and the answers, and then use the model to answer new questions from your users.
- Connect the bot to the Cortana channel and ask questions by using Cortana: This is not a way to create question and answer text, but a way to publish and use your chatbot. QnA Maker allows you to publish your knowledge base as a chatbot and connect it to various channels, such as web, mobile, or voice. You can connect your bot to the Cortana channel and ask questions by using Cortana, which is a voice-based virtual assistant.
Reference
Microsoft Learn > Azure > Cognitive Services > QnA Maker > QnA Maker documentation
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