  This paper connects a vector-based composition model to a formal semantics,
the Dependency-based Compositional Semantics (DCS). We show theoretical
evidence that the vector compositions in our model conform to the logic of DCS.
Experimentally, we show that vector-based composition brings a strong ability
to calculate similar phrases as similar vectors, achieving near
state-of-the-art on a wide range of phrase similarity tasks and relation
classification; meanwhile, DCS can guide building vectors for structured
queries that can be directly executed. We evaluate this utility on sentence
completion task and report a new state-of-the-art.
