  A major challenge of semantic parsing is the vocabulary mismatch problem
between natural language and target ontology. In this paper, we propose a
sentence rewriting based semantic parsing method, which can effectively resolve
the mismatch problem by rewriting a sentence into a new form which has the same
structure with its target logical form. Specifically, we propose two
sentence-rewriting methods for two common types of mismatch: a dictionary-based
method for 1-N mismatch and a template-based method for N-1 mismatch. We
evaluate our entence rewriting based semantic parser on the benchmark semantic
parsing dataset -- WEBQUESTIONS. Experimental results show that our system
outperforms the base system with a 3.4% gain in F1, and generates logical forms
more accurately and parses sentences more robustly.
