  For building question answering systems and natural language interfaces,
semantic parsing has emerged as an important and powerful paradigm. Semantic
parsers map natural language into logical forms, the classic representation for
many important linguistic phenomena. The modern twist is that we are interested
in learning semantic parsers from data, which introduces a new layer of
statistical and computational issues. This article lays out the components of a
statistical semantic parser, highlighting the key challenges. We will see that
semantic parsing is a rich fusion of the logical and the statistical world, and
that this fusion will play an integral role in the future of natural language
understanding systems.
