How to Extract Entities and Build a Knowledge Graph with Memgraph and SpaCy

The process of building a knowledge graph using Memgraph and SpaCy involves extracting entities from unstructured text and connecting them through relationships generated by GPT-4. The example used is "The Catcher in the Rye," where key entities are identified using SpaCy, and relationships are constructed by GPT-4, then visualized in Memgraph. The setup requires Docker to run Memgraph, SpaCy for entity extraction, and OpenAI's API for relationship generation. The text is tokenized and analyzed with SpaCy, and the extracted entities are processed into a JSON format representing nodes and relationships. These are transformed into Cypher queries to create the graph in Memgraph, allowing visualization and further analysis of the data through Memgraph Lab. The guide emphasizes setting up the environment, securing API keys, and using additional tools like Neo4j’s driver to connect to Memgraph, thus enabling users to explore and analyze the generated knowledge graph comprehensively.