  In this paper we present a system that exploits different pre-trained
Language Models for assigning domain labels to WordNet synsets without any kind
of supervision. Furthermore, the system is not restricted to use a particular
set of domain labels. We exploit the knowledge encoded within different
off-the-shelf pre-trained Language Models and task formulations to infer the
domain label of a particular WordNet definition. The proposed zero-shot system
achieves a new state-of-the-art on the English dataset used in the evaluation.
