Temporal Signals Help Label Temporal Relations

Leon Derczynski and Robert Gaizauskas

The 51st Annual Meeting of the Association for Computational Linguistics - Short Papers (ACL Short Papers 2013)
Sofia, Bulgaria, August 4-9, 2013

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Abstract

Automatically determining the temporal order of events and times in a text is difficult, though humans can readily perform this task. Sometimes events and times are related through use of an explicit co-ordination which gives information about the temporal relation: expressions like before and as soon as. We investigate the role that these co-ordinating temporal signal have in determining the type of temporal relations in discourse. Using machine learning we improve upon prior approaches to the problem, achieving over 80% accuracy at labelling the types of temporal relation between events and times annotated in text.

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