This paper investigates the use of first person plural pronouns as a rhetorical device in political speeches. We present an annotation schema for disambiguating pronoun references and use our schema to create an annotated corpus of debates from the German Bundestag. We then use our corpus to learn to automatically resolve pronoun referents in parliamentary debates. We explore the use of data augmentation with weak supervision to further expand our corpus and report preliminary results.

翻译：本文探讨在政治演讲中使用第一人称多元名作为言辞工具的问题,我们用一个注解词来混淆代名词的提法,用我们的计谋来从德国联邦议院建立一系列附加说明的辩论,然后我们用我们的编程来学习自动解决议会辩论中的代言词。我们探索如何在微弱监督下利用数据增强来进一步扩大我们的代言词,并报告初步结果。