Before revision:  Then , we propose  a novel knowledge distillation framework for knowledge graph embedding, utilizing multiple low-dimensional  KGE models as teachers  . Under a novel iterative distillation strategy, the MulDE modelproduces soft labels according to training epochs and student performance adaptively .
After revision:  Then , we propose a novel knowledge distillation framework for knowledge graph embedding, utilizing multiple low-dimensional hyperbolic KGE models as teachers . Under a novel iterative distillation strategy, the MulDE modelproduces soft labels according to training epochs and student performance adaptively .