基于跨场景推理的事件关系检测方法

事件关系检测是一项面向事件之间逻辑关系的自然语言处理技术。事件关系识别的核心任务是以事件为基本语义单元,通过分析事件的篇章结构信息及语义特征,实现事件逻辑关系的深层检测。该文首次建立一套事件关系检测的任务和研究体系,包括任务定义、关系体系划分、语料采集与标注、评价方法等。同时,该文提出了一种跨场景推理的事件关系检测方法,该方法认为,具有相同事件场景的“事件对”,往往具有相同的事件关系类型。该文提出的基于跨场景推理的事件关系检测方法在针对四大类事件关系类型的检测精确率为54.21%。

Detecting Event Relation through Cross-Scenario Inference

Event relation detection aims to detect a logical relation between pairwise events. The key to event relation detection is to detect latent logical relation between events by analyzing the corresponding discourse structure and semantic features of events, with the techniques of semantic relation recognition and inference. In this paper, we build an overall framework of the event relation detection task, including task definition, relation hierarchical structure, corpora acquisition and evaluation. Meanwhile, we propose a cross-scenario inference method to predict relation between pairwise events, which follows the basic hypothesis that if events express the same scenarios, they normally trigger similar relations. Finally, we experiment on four general semantic relations, Expansion, Comparison, Contingency and Temporal, achieving an accuracy of 54.21%.