  In this paper we generalize single-relation pseudo-Riemannian graph embedding
models to multi-relational networks, and show that the typical approach of
encoding relations as manifold transformations translates from the Riemannian
to the pseudo-Riemannian case. In addition we construct a view of relations as
separate spacetime submanifolds of multi-time manifolds, and consider an
interpolation between a pseudo-Riemannian embedding model and its Wick-rotated
Riemannian counterpart. We validate these extensions in the task of link
prediction, focusing on flat Lorentzian manifolds, and demonstrate their use in
both knowledge graph completion and knowledge discovery in a biological domain.
