A Model for Processing Temporal References in Chinese

Abstract

Conventional information systems cannot cater for temporal information effectively. For this reason, it is useful to capture and maintain the temporal knowledge (especially the relative knowledge) associated to each action in an information system. In this paper, we propose a model to mine and organize temporal relations embedded in Chinese sentences. Three kinds of event expressions are accounted for, i.e. single event, multiple events and declared event(s). Experiments are conducted to evaluate the mining algorithm using a set of news reports and the results are significant. Error analysis has also been performed opening up new doors for future research.