It assigns a real-valued score (or weight) to every derivation d ∈ D(x), where Λ ∈ R m assigns a relative importance to different aspects of the derivation independently captured by m feature functions The fully parameterised model can be seen as a discrete weighted set such that feature functions factorise over the steps in a derivation.
h k (d) = e∈d h k (e), where h k is a (local) feature function that assesses steps independently and d = e 1 , e 2 , .