Supervised structured large margin training approaches have been applied to parsing and produce promising results (Taskar et al., 2004;McDonald et al., 2005a;Wang et al., 2006).
structured large margin training can be expressed as minimizing a regularized loss (Hastie et al., 2004), as shown below: where Y i is the target tree for sentence X i ; L i,k ranges over all possible alternative k trees in , as shown in Section 2; and ∆(L i,k , Y i ) is a measure of distance between the two trees L i,k and Y i .