Automatic selection of HPSG-parsed sentences for treebank construction

Abstract

This article presents an ensemble parse approach to detecting and selecting high-quality linguistic analyses output by a hand-crafted HPSG grammar of Spanish implemented in the LKB system. The approach uses full agreement (i.e., exact syntactic match) along with a MaxEnt parse selection model and a statistical dependency parser trained on the same data. The ultimate goal is to develop a hybrid corpus annotation methodology that combines fully automatic annotation and manual parse selection, in order to make the annotation task more efficient while maintaining high accuracy and the high degree of consistency necessary for any foreseen uses of a treebank.

This work was supported by grant Ramón y Cajal from Spanish MICINN and the project METANET4U. We thank the reviewers for their comments and Carlos Morell for his support.