论文标题
事件图：事件提取作为语义图解析
EventGraph: Event Extraction as Semantic Graph Parsing
论文作者
论文摘要
事件提取涉及事件触发器和相应事件参数的检测和提取。现有系统通常将事件提取分解为多个子任务，而无需考虑其可能的相互作用。在本文中，我们提出了事件图，这是事件提取的联合框架，该框架将事件编码为图。我们将事件触发器和参数表示为语义图中的节点。因此，事件提取成为图形解析问题，该问题提供了以下优点：1）共同执行事件检测和参数提取； 2）从一段文本中检测和提取多个事件； 3）捕获事件参数与触发器之间的复杂互动。 ACE2005上的实验结果表明，我们的模型与最先进的系统具有竞争力，并且已经大大改善了参数提取的结果。此外，我们从ACE2005创建了两个新数据集，其中我们将整个文本跨越用于事件参数，而不仅仅是head Word。我们的代码和模型以开源方式发布。
Event extraction involves the detection and extraction of both the event triggers and corresponding event arguments. Existing systems often decompose event extraction into multiple subtasks, without considering their possible interactions. In this paper, we propose EventGraph, a joint framework for event extraction, which encodes events as graphs. We represent event triggers and arguments as nodes in a semantic graph. Event extraction therefore becomes a graph parsing problem, which provides the following advantages: 1) performing event detection and argument extraction jointly; 2) detecting and extracting multiple events from a piece of text; and 3) capturing the complicated interaction between event arguments and triggers. Experimental results on ACE2005 show that our model is competitive to state-of-the-art systems and has substantially improved the results on argument extraction. Additionally, we create two new datasets from ACE2005 where we keep the entire text spans for event arguments, instead of just the head word(s). Our code and models are released as open-source.
