We present an efficient approach for discourse parsing within and across sentences, where the unit of processing is an entire document, and not a single sentence. We apply shift-reduce algorithms for dependency and constituent parsing to determine syntactic dependencies for the sentences in a document, and subsequently a Rhetorical Structure Theory (RST) tree for the entire document. Our results show that our linear-time shiftreduce framework achieves high accuracy and a large improvement in efficiency compared to a state-of-the-art approach based on chart parsing with dynamic programming.
REF apply a transition based constituent parsing approach to construct a RST tree for a document.
Analysis of Discourse Structure with Syntactic Dependencies and Data-Driven Shift-Reduce Parsing
Proceedings of the 11th International Conference on Parsing Technologies (IWPT’09)
Computer Science