The current supervised relation classification (RC) task uses a single embedding to represent the relation between a pair of entities. We argue that a better approach is to treat the RC task as span-prediction (SP) problem, similar to Question answering (QA). We present a span-prediction based system for RC and evaluate its performance compared to the embedding based system. We demonstrate that the supervised SP objective works significantly better then the standard classification based objective. We achieve state-of-the-art results on the TACRED and SemEval task 8 datasets.

翻译：目前监督关系分类(RC)任务使用单一嵌入方式来代表一对实体之间的关系,我们认为,一个更好的办法是将RC任务作为跨边界(SP)问题处理,类似于问答(QA),我们为RC提出了一个基于跨边界的系统,并比基于嵌入的系统评估其绩效。我们证明,监督的SP目标比基于标准分类的目标效果好得多。我们在TRRED和SemEval任务8数据集上取得了最先进的成果。