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Document Title: Answers vNext v2

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titlebeta

Answers vNext Version: V2

Creation Date:

Author:

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titleORBITA

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Info

What does the beta label mean? Orbita Answers vNext

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launched in version 4.0.90 in September 2021 with certain known limitations. These limitations are:

  • Migration Support - You cannot migrate Answers v1 Knowledge Bases to Answers vNext. Migration support is in progress and will be available when the

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    label is removed from the product. If you have an Answers v1 Knowledge Base that you would like to have migrated to Answers vNext, please reach out to your Customer Success account manager to discuss.

  • Custom Schemas - Answers v1 supported knowledge bases leveraging custom schemas. Answers vNext does not support this yet. Support for custom schemas is in progress and will be available when the

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    label is removed from the product.

  • Documentation -While there is documentation available to support Answers vNext

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    , forthcoming documentation will be provided to support migration and configuration options.

User experience simplified

We understood that it’s difficult to get started with Orbita Answers and it often takes organizations many weeks to implement a question/answer experience using Orbita Answers because of the steep learning curve. It requires knowledge of the knowledge base, content structures, architecture, etc to effectively use Answers. To address these issues we have simplified the user experience to place a greater emphasis on usability without getting into too many details. The Answers author will see only the content that is relevant to create an effective Knowledge base and have the ability to organize the content in a tree view for better comprehension.

Answers vNext landing page

You can create a new KB using the “Create a Knowledge Base“ button. All the KBs will be listed here.

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Header Title

Description

Knowledge Base

The name of the Knowledge Base

Type

The content schema used while creating the KB.

Channels

The Channels such as text, voice, and screen in which the content can be handed out.

Primary Questions

Shows the primary question.

Answers

Shows type of answers content created ( Text, voice, screen/image)

Last Updated

Shows when the fact has updated

Build tab

This tab lists all the facts you authored in a table format.

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Header Title

Description

Primary Question

Shows the Primary question.

Labels

Lists all the labels created for each Primary question.

Variations

Shows the count of question variations created included.

Answers

Shows type of answers content created ( Text, voice, screen/image)

Last Updated

Shows when the fact has updated

Organize tab

The questions in the KB can be organized in a tree view in this tab.

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Advanced tab

This tab includes Settings, and Import, Export of the CSV files.

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Refer How do I create a .csv file for Answers vNext? for details on how the .csv file is structured.

Question & Answer Details page

This is where you define your Question, Answers, Labels, Question variations, and so on.

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Primary question

Primary Question is the canonical question for each Question & Answer.

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You can search the intent library for the same intent ID.

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Label

Though not mandatory, it is highly recommended to add Labels for each Question & Answer.

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Synonyms of a label are added to the respective slot line item as synonyms.

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Synonyms

You can add synonyms to the Labels using the Synonyms button at the top right corner of the page while editing the contents of the KB.

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Info

You should publish the interaction model to Google or Alexa after making changes to the Primary question, question variations, Labels, or synonyms.
Refer, How to Publish the interaction model to Dialogflow? and How do I Publish the interaction model to Amazon Alexa

Architecture

For example, consider the below scenarios where you have the questions as shown in the screenshot below.

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  1. The chatbot user asks an unambiguous question “What is diabetes?” as the utterance is associated with the Primary question (or one of its variations) the question context is set to this primary question.
    Here, if the user utterance is “diabetes“ then the label intent will get triggered. Since the diabetes label is associated with only one primary question, the question context is set to this primary question.

    1. The chatbot user then asks “What are the symptoms?“. This will trigger the label intent and since the label “Symptoms” is associated with two different Primary questions, it is an ambiguous question.
      Here, since there is not a single answer to this question, the chatbot will ask the user to rephrase the question.

  2. The chatbot user asks a question “What is cancer?” which triggers a primary question and sets the context.

    1. The chatbot user then asks “What are the symptoms?“, the bot will now understand that the chatbot user is asking about the “symptoms of cancer” and provides the respective answer.

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