Knowledge Graphs

Knowledge graphs organize facts as entities, relations, and often schemas or provenance, making information from different sources easier to connect, query, and inspect. Work spans graph construction from text and databases, entity alignment and completion, and reasoning with ontologies, rules, embeddings, and graph neural networks. Large language models are increasingly used to build and query graphs, often combining graph traversal with retrieval to answer multi-hop questions in domains such as medicine, science, and law. A central challenge is ensuring graphs are complete, consistent, and well-evidenced at scale; benchmarks also need to test genuine multi-hop reasoning rather than simpler link prediction, while preserving the traceability that makes graph-based answers useful.