We propose a complete probabilistic discriminative framework for performing sentencelevel discourse analysis. Our framework comprises a discourse segmenter, based on a binary classifier, and a discourse parser, which applies an optimal CKY-like parsing algorithm to probabilities inferred from a Dynamic Conditional Random Field. We show on two corpora that our approach outperforms the state-of-the-art, often by a wide margin.
A Novel Discriminative Framework for Sentence-Level Discourse Analysis
Shafiq Joty, Giuseppe Carenini, and Raymond Ng. In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL'12) , pages 904-915, 2012.
PDF Abstract BibTex Slides