- Knowledge Graph Population
Extracted entities and relations are synthesized into an ontology-aligned knowledge graph and linked with existing structured data. Gaps are incrementally enriched through machine learning and human curation.
- Knowledge Graph Storage
Specialized graph databases called triplestores (supporting RDF triples) provide efficient storage and querying of interconnected entities. Popular options include Neo4j, Stardog, GraphDB and Amazon Neptune.
- Querying and Analysis
Graph queries unlock insights through techniques like pathfinding, pattern matching, link prediction and community detection within knowledge graphs.