Several members of the lab got invited to write a contributions to the proceedings of the GKR2020 workshop. In this paper, we propose an additional metric to be used for the evaluation of approximate knowledge graph query answering. We also propose a graph embedding model based on axis-aligbned hyperrectangles that seems weel suited for this task.

The paper is availble as an open access publication from the proceedings published in the Lecture Notes Artificial Intelligence series.