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首页> 外文期刊>Mathematical structures in computer science >A generalised quantifier theory of natural language in categorical compositional distributional semantics with bialgebras
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A generalised quantifier theory of natural language in categorical compositional distributional semantics with bialgebras

机译:双曲线分类组成分布语义中的自然语言广义量化理论

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摘要

Categorical compositional distributional semantics is a model of natural language; it combines the statistical vector space models of words with the compositional models of grammar. We formalise in this model the generalised quantifier theory of natural language, due to Barwise and Cooper. The underlying setting is a compact closed category with bialgebras. We start from a generative grammar formalisation and develop an abstract categorical compositional semantics for it, and then instantiate the abstract setting to sets and relations and to finite-dimensional vector spaces and linear maps. We prove the equivalence of the relational instantiation to the truth theoretic semantics of generalised quantifiers. The vector space instantiation formalises the statistical usages of words and enables us to, for the first time, reason about quantified phrases and sentences compositionally in distributional semantics.
机译:分类组成分布语义是一种自然语言的模型;它结合了与语法的组成模型的单词统计矢量空间模型。我们在这型模型中正式化了自然语言的广义量化理论,由于BarWise和Cooper。底层设置是具有双曲线的紧凑封闭类别。我们从生成语法形式化开始,并为其开发抽象的分类组成语义,然后将抽象设置实例化到集合和关系以及有限维矢量空间和线性地图。我们证明了一般性量词的真理理论语义的关系实例化的等价性。传染媒介空间实例化正规规范言论的统计用法,并首次启用我们在分布语义中组成的量化短语和句子。

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