As mentioned before, MSTParser is a graphbased statistical dependency parser, whose learning procedure can be viewed as the assignment of different weights to all kinds of dependency arcs.
the feature model focuses on each kind of head-child pair in the dependency tree, and mainly contains four categories of features (Mcdonald et al., 2005a): basic uni-gram features, basic bi-gram features, in-between POS features, and surrounding POS features.