论文标题
“你想做什么？”事件过程的语义键入
"What Are You Trying to Do?" Semantic Typing of Event Processes
论文作者
论文摘要
本文研究了一种新的认知动机的语义分型任务，多轴事件过程键入，在事件过程中，试图推断自由形式类型的标签描述（i）该过程所做的动作类型以及（ii）该过程试图影响的对象类型。该任务的灵感来自事件理解的计算和认知研究，这表明理解事件的过程通常是通过认识主人公的目标，计划或意图来指导的。我们开发了一个大型数据集，其中包含超过60k的事件过程，其中包含非常大的（$ 10^3 \ sim 10^4 $）标签词汇的操作和对象类型轴上的超细粒键入。然后，我们提出了一个混合学习框架P2GT，该框架通过Glosses1和联合学习到级框架的间接监督解决了具有挑战性的打字问题。正如我们的实验指出的那样，P2GT支持确定过程的意图以及受影响对象的精细语义类型。它还证明了处理几例案例的能力，以及对室外事件过程的强有力的推广性。
This paper studies a new cognitively motivated semantic typing task, multi-axis event process typing, that, given an event process, attempts to infer free-form type labels describing (i) the type of action made by the process and (ii) the type of object the process seeks to affect. This task is inspired by computational and cognitive studies of event understanding, which suggest that understanding processes of events is often directed by recognizing the goals, plans or intentions of the protagonist(s). We develop a large dataset containing over 60k event processes, featuring ultra fine-grained typing on both the action and object type axes with very large ($10^3\sim 10^4$) label vocabularies. We then propose a hybrid learning framework, P2GT, which addresses the challenging typing problem with indirect supervision from glosses1and a joint learning-to-rank framework. As our experiments indicate, P2GT supports identifying the intent of processes, as well as the fine semantic type of the affected object. It also demonstrates the capability of handling few-shot cases, and strong generalizability on out-of-domain event processes.
