Pre-trained Language Model with Prompts for Temporal Knowledge Graph Completion

arXiv:2305.07912v2 Announce Type: replace
Abstract: Temporal Knowledge graph completion (TKGC) is a crucial task that involves reasoning at known timestamps to complete the missing part of facts and has attracted more and more attention in recent years. Most existing methods focus on learning representations based on graph neural networks while inaccurately extracting information from timestamps and insufficiently utilizing the implied information in relations. To address these problems, we propose a novel TKGC model, namely Pre-trained Language Model with Prompts for …

abstract arxiv attention cs.ai cs.cl facts focus graph graph neural networks knowledge knowledge graph language language model networks neural networks part prompts reasoning temporal type