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The semantics of natural language has a highly-structured logical aspect. For example, the meaning of the question â€œWhat is the third tallest mountain in a state not bordering California?â€ involves superlatives, quantification, and negation. In this talk, we develop a new representation of semantics called Dependency-Based Compositional Semantics (DCS) which can represent these complex phenomena in natural language. At the same time, we show that we can treat the DCS structure as a latent variable and learn it automatically from question/answer pairs. This allows us to build a compositional question-answering system that obtains state-of-the-art accuracies despite using less supervision than previous methods. I will conclude the talk with extensions to handle contextual effects in language.
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