KG Construction
KG: Knowledge Graph
Overview
Knowledge graph construction studies how to turn information from documents, databases, tables, and images into connected, queryable facts. Methods combine named-entity and relation extraction, entity linking and deduplication, and schema or ontology design; newer systems also use large language models and agents, often with expert review and symbolic validation. Provenance, confidence, temporal context, and incremental updates help keep graphs auditable and useful for tasks such as scientific search, clinical reasoning, and question answering. A central challenge is balancing coverage, accuracy, consistency, and construction cost: flexible extraction can capture more information, but schemas, canonicalization, and evidence checks are needed to prevent unsupported or mismatched facts.
Latest papers
195 papers20 papers in the last four weeks, up 18% on the four weeks before. 0.1% of all new papers.