Paper: Exploiting Discourse Analysis for Article-Wide Temporal Classification

ACL ID D13-1002
Title Exploiting Discourse Analysis for Article-Wide Temporal Classification
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

In this paper we classify the temporal relations between pairs of events on an article-wide ba- sis. This is in contrast to much of the exist- ing literature which focuses on just event pairs which are found within the same or adjacent sentences. To achieve this, we leverage on dis- course analysis as we believe that it provides more useful semantic information than typical lexico-syntactic features. We propose the use of several discourse analysis frameworks, in- cluding 1) Rhetorical Structure Theory (RST), 2) PDTB-styled discourse relations, and 3) topical text segmentation. We explain how features derived from these frameworks can be effectively used with support vector machines (SVM) paired with convolution kernels. Ex- periments show that our proposal is effective in improving on the...