Paper: A Constituent-Based Approach to Argument Labeling with Joint Inference in Discourse Parsing

ACL ID D14-1008
Title A Constituent-Based Approach to Argument Labeling with Joint Inference in Discourse Parsing
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

Discourse parsing is a challenging task and plays a critical role in discourse anal- ysis. In this paper, we focus on label- ing full argument spans of discourse con- nectives in the Penn Discourse Treebank (PDTB). Previous studies cast this task as a linear tagging or subtree extraction problem. In this paper, we propose a novel constituent-based approach to argu- ment labeling, which integrates the ad- vantages of both linear tagging and sub- tree extraction. In particular, the pro- posed approach unifies intra- and inter- sentence cases by treating the immediate- ly preceding sentence as a special con- stituent. Besides, a joint inference mech- anism is introduced to incorporate glob- al information across arguments into our constituent-based approach via integer lin- ear programming. E...