There has recently been some interest among computational linguists in the task of inducing grammar-based "semantic parsers" from sets of paired strings and meaning representations, following pioneering work by Zettlemoyer and Collins (2005). Work of this kind is currently limited by the paucity of datasets for training. The talk reviews the state of the art in this field, then proposes a way to semi-automatically generate much larger language-independent datasets, on the same order of magnitude as syntactic treebanks, using linguistic knowledge that has only recently begun to become available, for use in inducing semantic parsers for under-resourced languages for application in statistical machine translation.