We present an event structure classification empirically derived from inferential properties annotated on sentence- and document-level Universal Decompositional Semantics (UDS) graphs. We induce this classification jointly with semantic role, entity, and event-event relation classifications using a document-level generative model structured by these graphs. To support this induction, we augment existing annotations found in the UDS1.0 dataset, which covers the entirety of the English Web Treebank, with an array of inferential properties capturing fine-grained aspects of the temporal and aspectual structure of events. The resulting dataset (available at decomp.io) is the largest annotation of event structure and (partial) event coreference to date.
翻译:我们提出了一个从判决和文件一级通用分解语义图(UDS)附加说明的推断属性得出的事件结构分类。我们使用由这些图表构建的文件级变异模型,将这种分类与语义作用、实体和事件-事件关系分类结合起来。为了支持这一感应,我们补充了UDS1.0数据集中的现有说明,该数据集涵盖整个英文网络树库,一系列推断属性反映了事件的时间和侧面结构的细微差别方面。由此产生的数据集(可在 decomp.io查阅)是迄今为止事件结构和(部分)事件参照的最大说明。