An Ensemble Model that Combines Syntactic and Semantic Clustering for Discriminative Dependency Parsing
Gholamreza Haffari, Marzieh Razavi, Anoop Sarkar · 2011
We combine multiple word representations based on semantic clusters extracted from the (Brown et al., 1992) algorithm and syntactic clusters obtained from the Berkeley parser (Petrov et al., 2006) in order to improve discriminative dependency parsing in the MST-Parser framework (McDonald et al., 2005). We also provide an ensemble method for combining diverse cluster-based models. The two contributions together significantly improves unlabeled dependency accuracy from 90.82% to 92.13%. 1