Forge Capsule

Knowledge Graph Construction: Entity Extraction and Relationship Mapping

Knowledge graph construction pipeline: NER (named entity recognition) → coreference resolution → relation extraction → ontology alignment → graph population. Tools: spaCy, Stanford NLP, REBEL (relation extraction). Ontologies: Schema.org, DBpedia, Wikidata, domain-specific (SNOMED CT, MeSH for medical). Embedding: TransE, RotatE, ComplEx for KG completion. Graph neural networks for link prediction: GraphSAGE, GAT, R-GCN. Temporal KGs: model time-evolving facts. Knowledge graph quality: completeness, consistency, timeliness. Production systems: Google Knowledge Graph (1B+ entities), Microsoft Satori, Amazon Product Graph. Forge uses Neo4j with capsule nodes and typed semantic edges.