OVERVIEW
Virtual Assistants
Kore.ai Platform
Key Concepts
Natural Language Processing (NLP)
Accessing Platform
VIRTUAL ASSISTANTS
Virtual Assistant Builder
Virtual Assistant Types
Getting Started
Creating a Simple Bot
SKILLS
Storyboard
Dialog Task
Introduction
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Dialog Builder (Legacy)
User Intent Node
Dialog Node
Entity Node
Supported Entity Types
Composite Entities
Supported Colors
Supported Company Names
Form Node
Logic Node
Message Nodes
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Bot Action Node
Service Node
Custom Authentication
2-way SSL for Service nodes
Script Node
Agent Transfer Node
WebHook Node
Grouping Nodes
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User Prompts
Knowledge Graph
Terminology
Building
Generation
Importing and Exporting
Analysis
Knowledge Extraction
Build
Alert Tasks
Introduction
Ignore Words and Field Memory
How to Schedule a Smart Alert
Small Talk
Digital Views
Overview
Configuring Digital Views
Digital Forms
Overview
How to Configure Digital Forms
NATURAL LANGUAGE
Overview
Machine Learning
Introduction
Model Validation
Fundamental Meaning
Introduction
NLP Guidelines
Knowledge Graph
Traits
Introduction
How to Use Traits
Ranking and Resolver
Advanced NLP Configurations
INTELLIGENCE
Overview
Context Management
Overview
Session and Context Variables
Context Object
How to Manage Context Switching
Manage Interruptions
Dialog Management
Sub-Intents & Follow-up Intents
Amend Entity
Multi-Intent Detection
Sentiment Management
Tone Analysis
Sentiment Management
Event Based Bot Actions
Default Conversations
Default Standard Responses
TEST & DEBUG
Talk to Bot
Utterance Testing
Batch Testing
Conversation Testing
CHANNELS
PUBLISH
ANALYZE
Overview
Dashboard
Custom Dashboard
Overview
How to Create Custom Dashboard
Conversation Flows
NLP Metrics
ADVANCED TOPICS
Universal Bots
Overview
Defining
Creating
Training
Customizing
Enabling Languages
Store
Smart Bots
Defining
koreUtil Libraries
SETTINGS
Authorization
Language Management
PII Settings
Variables
Functions
IVR Integration
General Settings
Management
Import & Export
Delete
Versioning
Collaborative Development
PLAN & USAGE
Overview
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Invoices
API GUIDE
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API List
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SDKs
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Web SDK Tutorial
Message Formatting and Templates
Mobile SDK Push Notification
Widget SDK Tutorial
Widget SDK – Message Formatting and Templates
Web Socket Connect & RTM
Using the BotKit SDK
Installing
Configuring
Events
Functions
BotKit SDK Tutorial – Agent Transfer
BotKit SDK Tutorial – Flight Search Sample Bot
Using an External NLP Engine
ADMINISTRATION
HOW TOs
Creating a Simple Bot
Creating a Banking Bot
Context Switching
Using Traits
Schedule a Smart Alert
Configure UI Forms
Add Form Data into Data Tables
Configuring Digital Views
Add Data to Data Tables
Update Data in Data Tables
Custom Dashboard
Custom Tags to filter Bot Metrics
Patterns for Intents & Entities
Build Knowledge Graph
Global Variables
Content Variables
Using Bot Functions
Configure Agent Transfer
Update Balance Task
Transfer Funds Task
RELEASE NOTES
  1. Docs
  2. Virtual Assistants
  3. Builder
  4. Knowledge Graph
  5. Generation of Knowledge Graph

Generation of Knowledge Graph

The performance of Kore.ai’s Knowledge Graph is based on the proper organization of the Knowledge Graph-based upon key domain terms and establishing a hierarchy.

Building the FAQs is easy when you start fresh with the Knowledge Graph, but in case you have a list of questions-answer pairs converting the same into a fully functional Knowledge Graph is a tedious task.

Kore.ai’s Knowledge Graph Generator automatically extracts terms from FAQs, defines the hierarchy between these terms, and also associates the FAQs to the right terms. You can then import the output file from the generator to your bot’s Knowledge Graph without having to worry about the hierarchy. You can also edit the hierarchy after import to suit your needs. It is highly recommended to review and make changes as the Knowledge Graph generated is a suggestion alone.

NOTE: Knowledge Graph Generator is available from v7.1 of the platform.

The Kore.ai Knowledge Graph Generator is hosted on the Kore GitHub repository. This document gives the steps in the installation and usage of the generator.

Prerequisites

  • Python 3.6: The Knowledge Graph Generator requires python v3.6. You can download it here.
  • Virtual Environment: It is advised to use a virtual environment, instead of installing requirements in the system directly. Follow the steps mentioned here to set up a virtual environment.
  • For Windows Developers:
    • Microsoft Visual C++ Build Tools – tested with v14.0.
    • Windows 10 users must install Windows 10 SDK. You can download it here.
    • The operating system must be up to date for a seamless installation of requirements. Some libraries like SpiCy (internal dependency) need specific DLLs that are available in the latest updates.
  • A file containing the FAQs in JSON or CSV format. You can obtain this file in two ways:
    • Export the Knowledge Graph from Kore.ai Bot Builder platform, see here for how.
    • Build the Knowledge Graph in a tabular form with questions in the first column and answers in the corresponding second column and save the file in CSV format.

Configuration

  1. Download the Knowledge Graph Generator from Kore.ai GitHub: https://github.com/Koredotcom/KnowledgeGraphGenerator.
  2. Extract the zip file into a folder and open the command prompt from that generator folder.
  3. Activate the virtual environment: Execute the following command replacing the placeholders with actual values to activate the virtual environment:
    • For Windows:
      <virtual_environments_folder_location>/<virtualenv_name>/Scripts/activate
    • For Unix/macOS:
      <virtual_environments_folder_location>/<virtualenv_name>/bin/activate.

    Once the virtual environment is activated, you can see the virtual environment name at the start of every command in the console.

  4. Install the requirements: Run the following command from your project root directory (KnowledgeGraphGenerator) in the virtual environment to install the requirements
    pip install -r requirements.txt
    You can verify the installation by running the following command and ensuring that the list contains all the components mentioned in the requirement.txt file.
    pip list
  5. Download spacy English model: Run the following command to download spaCy, the NLP model.
    python -m spacy download en

Execution

Now that you have the prerequisites and have configured the Knowledge Graph Generator, let us see how to generate the Knowledge Graph.

The following command executes the generator:

python KnowledgeGraphGenerator.py --file_path <INPUT_FILE_PATH> --type <INPUT_FILE_TYPE> --language <LANGUAGE_CODE> --v <true/false>

Let us look at each of the options:

Option Description Mandatory/Optional Default Value
Input File Path Input file name along with the location Mandatory
Input File Type The type of input file:

  • json_export – for files exported from Kore.ai Bot Builder using JSON Export option
  • csv_export – for files exported from Kore.ai Bot Builder using CSV Export option
  • CSV – for files with questions in the first column and answers in the respective second column
Mandatory
Language Code The language code for the language in which input data exist Optional en (English)
Verbose Mode Running a command in verbose mode to see intermediate progress steps Optional false

Output

The output JSON file is generated and placed under the project root directory with the name ao_output.json

The output JSON file can directly be imported to Knowledge Graph in the bot. See here for steps to import Knowledge Graph.

NOTE: When you try to import the Knowledge Graph it replaces the existing one. We recommend you take a back up before importing.

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