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.
翻译:在本文中,我们提出了一个系统,在没有任何监督的情况下,利用经过事先培训的不同语言模型向WordNet的同步点分配域名标签;此外,该系统不限于使用一套特定的域名标签;我们利用在经过培训的不同现成语文模型和任务配方中编码的知识,推导出WordNet特定定义的域名标签;提议的零弹式系统在评估中使用的英文数据集方面达到了新的最新水平。