I read "Using String Kernels for Learning Semantic Parsers" (Kate, 2006) as a related paper. While much in the spirit of this week's paper, it uses beam search over CFG derivations in a meaning representation language with a string kernel SVM at each node in the parse tree to perform semantic parsing. The parsing algorithm is a modified Early Parser. In general, I found their approach very satisfying, though it certainly was not as expressive as a CCG with unification. At the same time, I liked the simplicity of this model. Further, this model held up reasonably well when noise was injected to simulate speech recognizer errors.