A Divide-and-Conquer Strategy for Parsing
Peh Li Shiuan, Christopher Ting Hian Ann
Abstract
In this paper, we propose a novel strategy which is designed to enhance the accuracy of the parser by simplifying complex sentences before parsing. This approach involves the separate parsing of the constituent sub-sentences within a complex sentence. To achieve that, the divide-and-conquer strategy first disambiguates the roles of the link words in the sentence and segments the sentence based on these roles. The separate parse trees of the segmented sub-sentences and the noun phrases within them are then synthesized to form the final parse. To evaluate the effects of this strategy on parsing, we compare the original performance of a dependency parser with the performance when it is enhanced with the divide-and-conquer strategy. When tested on 600 sentences of the IPSM'95 data sets, the enhanced parser saw a considerable error reduction of 21.2% in its accuracy.
Create a lesson
Related papers
A Memory-Based Approach to Learning Shallow Natural Language Patterns
Shlomo Argamon, Ido Dagan, Yuval Krymolowski
A Comparison of WordNet and Roget's Taxonomy for Measuring Semantic Similarity
Michael Mc Hale
Some Ontological Principles for Designing Upper Level Lexical Resources
Nicola Guarino
Towards an implementable dependency grammar
Timo Jarvinen, Pasi Tapanainen
A Variant of Earley Parsing
Mark-Jan Nederhof, Giorgio Satta
Segregatory Coordination and Ellipsis in Text Generation
James Shaw