Graph Builder and Updater for publicly listed Companies

This project builds and dynamically updates a knowledge graph from Wikidata, incorporating information from news articles provided by The New York Times API. The project utilizes Neo4j as the graph database.

Features

• Knowledge Graph Construction: Builds a knowledge graph from Wikidata, starting with a list of seed companies and expanding outwards based on specified relationships and depth.
• Dynamic Updates: Continuously updates the knowledge graph with new information extracted from news articles.
• Configurable: Allows customization of the knowledge graph structure, including entity types, relationship depth, and date range.
• Efficient Caching: Implements a caching mechanism to reduce redundant Wikidata queries.
• Demo Graph: Provides an option to build a smaller demo graph for testing and experimentation.

Requirements

• Python 3.7+
• Neo4j (including a running Neo4j instance)
• A selection of Libraries (install via pip install -r requirements.txt):
  • neo4j~=5.0
  • colorama *configparser *google-generativeai *requests

Installation

1. Clone the repository: git clone <repository_url>
2. Navigate to the project directory: cd <project_directory>
3. Install the required libraries: pip install -r requirements.txt
4. Configure the Neo4j connection: Update the config.ini file with your Neo4j URI, username, and password. An example config.ini file is provided.

Configuration

The project is configured using the config.ini file:

[neo4j]
uri = neo4j://localhost:7687
username = neo4j
password = your neo4j password

[gemini]
api_key = your Gemini api key

[nytimes]
api_key = your NYTimes api key