  Semantic NLP applications often rely on dependency trees to recognize major
elements of the proposition structure of sentences. Yet, while much semantic
structure is indeed expressed by syntax, many phenomena are not easily read out
of dependency trees, often leading to further ad-hoc heuristic post-processing
or to information loss. To directly address the needs of semantic applications,
we present PropS -- an output representation designed to explicitly and
uniformly express much of the proposition structure which is implied from
syntax, and an associated tool for extracting it from dependency trees.
