Towards Multi-Relational Multi-Hop Reasoning over Dense Temporal Knowledge Graphs

Temporal knowledge graph reasoning has emerged as a crucial task for answering timedependent questions within a knowledge graph (KG). Despite tremendous progress, the present research is impeded by the sparsity of a temporal KG and an over-reliance on simple singlerelational reasoning patterns. To overcome these challenges, we introduce Mul 2 Questions, a new temporal KG reasoning benchmark featuring over 200k entities and 960k questions designed to facilitate complex, multi-relational and multi-hop reasoning. Additionally, we propose a new model adept at conducting patternaware and time-sensitive reasoning across temporal KGs. The model's efficacy is confirmed through rigorous evaluations, showcasing its effectiveness in sparse data conditions and adeptness at handling questions with long reasoning chains. We have made our benchmark and model publicly accessible at https://github.com/Zihe2003/Mul2Questions .