Our approach is also intuitively related to stacked learning (SL), a machine learning framework that has recently been applied to dependency parsing to integrate two main-stream parsing models, i.e., graph-based and transition-based models (Nivre and McDonald, 2008;Martins et al., 2008).
the SL framework trains two parsers on the same treebank and therefore does not need to consider the problem of annotation inconsistencies.