基于精选知识库的事件-对象推理：获取缺失信息
Event-Object Reasoning with Curated Knowledge Bases: Deriving Missing Information
摘要：
我们研究的更广泛的目标是制定关于知识库（如AURA）的为什么和如何问题的答案。当我们使用许多可用的知识库进行推理时，我们面临的一个问题是有时会丢失所需的信息。这种情况的示例包括部分缺失关于下一子事件、第一子事件、最后子事件、事件结果、事件输入、事件目的地和事件中涉及的原材料的信息。在许多情况下，人们可以通过推理恢复部分缺失的知识。在本文中，我们给出了一个正式的定义如何丢失的信息可以恢复，然后给出了一个ASP实现它。然后，我们讨论了这方面的含义，回答为什么和如何的问题。
英文摘要：
The broader goal of our research is to formulate answers to why and how questions with respect to knowledge bases, such as AURA. One issue we face when reasoning with many available knowledge bases is that at times needed information is missing. Examples of this include partially missing information about next sub-event, first sub-event, last sub-event, result of an event, input to an event, destination of an event, and raw material involved in an event. In many cases one can recover part of the missing knowledge through reasoning. In this paper we give a formal definition about how such missing information can be recovered and then give an ASP implementation of it. We then discuss the implication of this with respect to answering why and how questions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
