More-over, since LLGPar is a second-order model, the presence of certain dependencies can directly affect the choice of other dependencies through the scores of adjacent siblings.
given the same amount of annotated dependencies, random PA contains more syntactic information than random FA, which explains why LLGPar performs better with PA than FA.