  We describe a contextual parser for the Robot Commands Treebank, a new
crowdsourced resource. In contrast to previous semantic parsers that select the
most-probable parse, we consider the different problem of parsing using
additional situational context to disambiguate between different readings of a
sentence. We show that multiple semantic analyses can be searched using dynamic
programming via interaction with a spatial planner, to guide the parsing
process. We are able to parse sentences in near linear-time by ruling out
analyses early on that are incompatible with spatial context. We report a 34%
upper bound on accuracy, as our planner correctly processes spatial context for
3,394 out of 10,000 sentences. However, our parser achieves a 96.53%
exact-match score for parsing within the subset of sentences recognized by the
planner, compared to 82.14% for a non-contextual parser.
