Time in a Box: Advancing Knowledge Graph Completion with Temporal Scopes

Ling Cai, K. Janowicz, Bo Yan, Rui Zhu, Gengchen Mai
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引用次数: 7

Abstract

Almost all statements in knowledge bases have a temporal scope during which they are valid. Hence, knowledge base completion (KBC) on temporal knowledge bases (TKB), where each statementmay be associated with a temporal scope, has attracted growing attention. Prior works assume that each statement in a TKBmust be associated with a temporal scope. This ignores the fact that the scoping information is commonly missing in a KB. Thus prior work is typically incapable of handling generic use cases where a TKB is composed of temporal statements with/without a known temporal scope. In order to address this issue, we establish a new knowledge base embedding framework, called TIME2BOX, that can deal with atemporal and temporal statements of different types simultaneously. Our main insight is that answers to a temporal query always belong to a subset of answers to a time-agnostic counterpart. Put differently, time is a filter that helps pick out answers to be correct during certain periods. We introduce boxes to represent a set of answer entities to a time-agnostic query. The filtering functionality of time is modeled by intersections over these boxes. In addition, we generalize current evaluation protocols on time interval prediction. We describe experiments on two datasets and show that the proposed method outperforms state-of-the-art (SOTA) methods on both link prediction and time prediction.
盒子里的时间:用时间范围推进知识图谱的完成
知识库中的几乎所有语句都有一个有效的时间范围。因此,基于时态知识库(TKB)的知识库补全(KBC)引起了越来越多的关注,其中每个语句可能与时态范围相关联。以前的工作假设tkb中的每个语句都必须与一个时间范围相关联。这忽略了一个事实,即KB中通常缺少范围信息。因此,以前的工作通常无法处理TKB由具有/不具有已知时间范围的时态语句组成的通用用例。为了解决这个问题,我们建立了一个新的知识库嵌入框架TIME2BOX,它可以同时处理不同类型的时态和非时态语句。我们的主要见解是,时间查询的答案总是属于与时间无关的对应查询的答案的子集。换句话说,时间是一个过滤器,可以帮助挑选出在特定时期正确的答案。我们引入方框来表示一组与时间无关的查询的回答实体。时间的过滤功能由这些方框上的交叉点来建模。此外,我们还对现有的时间间隔预测评估方案进行了推广。我们描述了在两个数据集上的实验,并表明所提出的方法在链路预测和时间预测方面都优于最先进的(SOTA)方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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