To improve the cross-domain parsing performance, we propose a data-oriented model to explore the linguistic generality encoded in a hand-crafted, domainindependent, linguistically-precise English grammar, namely English Resource Grammar (ERG;Flickinger, 2000).
we introduce a cost-sensitive training model to learn crossdomain semantic information implicitly encoded in WikiWoods (Flickinger et al., 2010), i.e., a corpus that collects the wikipedia 1 texts as well as their automatic syntactico-semantic annotations produced by ERG.