Following <cite>Levy et al. (2017)</cite> , we distinguish between the traditional RE setting where the aim is to generalize to unseen entities (UnENT) and the zero-shot setting (UnREL) where the aim is to do so for unseen relation types (see Section 2). Our goal is to answer these three questions: A) how well can RE models be transferred across languages? B) in the difficult UnREL setting, can the variance between languages in the number of instances of relations (see Figure 2 ) be exploited to enable more robust RE ? C) can one jointly-trained multilingual model which performs RE in multiple languages perform comparably to or outperform its individual monolingual counterparts?