Coupled temporal scoping of relational facts

Recent research has made significant advances in automatically constructing knowledge bases by extracting relational facts (e.g., Bill Clinton-presidentOf-US) from large text corpora. Temporally scoping such relational facts in the knowledge base (i.e., determining that Bill Clinton-presidentOfUS is true only during the period 1993 - 2001) is an important, but relatively unexplored problem. In this paper, we propose a joint inference framework for this task, which leverages fact-specific temporal constraints, and weak supervision in the form of a few labeled examples. Our proposed framework, CoTS (Coupled Temporal Scoping), exploits temporal containment, alignment, succession, and mutual exclusion constraints among facts from within and across relations. Our contribution is multi-fold. Firstly, while most previous research has focused on micro-reading approaches for temporal scoping, we pose it in a macroreading fashion, as a change detection in a time series of facts’ features co...

• Type: Journal
• Year: 2012
• Where: WSDM
• Authors: Partha Pratim Talukdar, Derry Tanti Wijaya, Tom Mitchell
• Keywords: Data Mining, Inference Framework, Information Systems Applications, Unexplored Problem, WSDM 2012