A Divide-and-Conquer Strategy for Parsing

TL;DR

This paper introduces a divide-and-conquer approach to improve parsing accuracy by segmenting complex sentences into simpler parts, then combining their parse trees, resulting in a significant error reduction.

Contribution

It presents a novel sentence segmentation method based on link word roles to enhance dependency parsing accuracy.

Findings

Error rate reduced by 21.2% on IPSM'95 dataset

Effective disambiguation of link words improves parsing

Segmentation strategy enhances parser performance

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.