We built 3 datasets from our alternation data: FS -candidates generated from the f-structure; SEM n -realisations from the naive meaning representations; SEM h -candidates from the heuristically underspecified meaning representation.
we keep the set of original corpus sentences (=the target realisations) constant, but train and test the model on different candidate sets.