Given an input sentence, e, the task of semantic parsing is to find a derivation that yields e, f , so that f is a translation of e. Since there may be multiple derivations that yield e (and thus multiple possible translations of e), a mechanism must be devised for discriminating the correct derivation from the incorrect ones.
the semantic parsing model of WASP thus consists of an SCFG, G, and a probabilistic model, parameterized by λ, that takes a possible derivation, d, and returns its likelihood of being correct given an input sentence, e. the output translation, f ⋆ , for a sentence, e, is defined as: where m(d) is the MR string that a derivation d yields, and D(G|e) is the set of all possible derivations of G that yield e. the output MR is the yield of the most probable derivation that yields e in the NL stream.