The Leaf Path Projection View of Parse Trees: Exploring String Kernels for HPSG Parse Selection
We present a novel representation of parse trees as lists of paths (leaf projection paths) from leaves to the top level of the tree. This representation allows us to achieve significantly higher accuracy in the task of HPSG parse selection than standard models, and makes the application of string kernels natural. We define tree kernels via string kernels on projection paths and explore their performance in the context of parse disambiguation. We apply SVM ranking models and achieve an exact sentence accuracy of 85.40% on the Redwoods corpus.