As our baseline parsers, we use two state-of-the-art lexicalised parsing models , namely the Bikel parser (Bikel, 2004) and Charniak parser (Charniak, 2000).

While a detailed description of the respective parsing models is beyond the scope of this paper, it is worth noting that both parsers induce a context free grammar as well as a generative parsing model from a training set of parse trees, and use a development set to tune internal parameters.

(2005) experimented with first-sense and hypernym features from HowNet and CiLin (both WordNets for Chinese) in a generative parse model applied to the Chinese Penn Treebank.

Tighter integration of semantics into the parsing models , possibly in the form of discriminative reranking models (Collins and Koo, 2005; Chamiak and J ohn-son, 2005; McClosky et al., 2006), is a promising way forward in this regard.

Given our simple procedure for incorporating lexical semantics into the parsing process, our hope is that this research will open the door to further gains using more sophisticated parsing models and richer semantic options.

Directions for future research include a more detailed analysis of the effect of feature-based integration, as well as the exploration of other strategies for integrating different parsing models .

Many of these parsers are based on data-driven parsing models , which learn to produce dependency graphs for sentences solely from an annotated corpus and can be easily ported to any

The combined parsing model is essentially an instance of the graph-based model, where arc scores are derived from the output of the different component parsers.