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:

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.