Future research directions in knowledge graph completion include: (1) combining logical rules containing rich background information and knowledge graph (KG) triples in a unified framework (e.g., jointly embedding KGs and logical rules); (2) exploring open-world KG completion models to connect unseen entities, addressing the limitation of closed-world assumptions in recent models; and (3) investigating efficient approaches applicable to large-scale KGs with millions of entities and relations.