Analysis and refinement of temporal relation aggregation

Abstract

To obtain a complete temporal picture of a relation it is necessary to aggregate fragments of temporal information across relation instances in text. This process is non-trivial even for humans because temporal information can be imprecise and inconsistent, and systems face the additional challenge that each of their classifications is potentially false. Even a small amount of incorrect proposed temporal information about a relation can severely affect the resulting aggregate temporal knowledge. We motivate and evaluate three methods to modify temporal relation information prior to aggregation to address this challenge.