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

Learning Semantically and Additively Compositional Distributional Representations