We describe the design and use of the CREER dataset, a large corpus annotated with rich English grammar and semantic attributes. The CREER dataset uses the Stanford CoreNLP Annotator to capture rich language structures from Wikipedia plain text. This dataset follows widely used linguistic and semantic annotations so that it can be used for not only most natural language processing tasks but also scaling the dataset. This large supervised dataset can serve as the basis for improving the performance of NLP tasks in the future.
翻译:我们描述CREER数据集的设计和使用情况,CREER数据集是具有丰富的英语语法和语义属性的大型数据组。CREER数据集使用斯坦福核心NLP说明器从维基百科纯文本中捕捉丰富的语言结构。该数据集遵循广泛使用的语言和语义说明,不仅可用于大多数自然语言处理任务,还可以用于缩放数据集。这个大型受监督数据集可以作为改进未来NLP任务绩效的基础。