Relation Prediction Task

Relation prediction, a core task in knowledge graph completion, aims to identify missing relationships between entities within a knowledge graph. Current research focuses on improving prediction accuracy and efficiency using various approaches, including transformer-based models that leverage subgraph information and connection-biased attention, as well as incorporating external knowledge sources like pre-trained language models and textual descriptions. These advancements are crucial for enhancing knowledge graph quality, which has significant implications for applications such as question answering, recommendation systems, and biomedical research.