This paper describes a compositional distributional method to generate contextualized senses of words and identify their appropriate translations in the target language using monolingual corpora. Word translation is modeled in the same way as contextualization of word meaning, but in a bilingual vector space. The contextualization of meaning is carried out by means of distributional composition within a structured vector space with syntactic dependencies, while the bilingual space is created by means of transfer rules and a bilingual dictionary. A phrase in the source language, consisting of a head and a dependent, is translated into the target language by selecting both the nearest neighbor of the head given the dependent, and the nearest neighbor of the dependent given the head. This process is expanded to larger phrases by means of incremental composition. Experiments were performed on English and Spanish monolingual corpora in order to translate phrasal verbs in context. A new bilingual dataset to evaluate strategies aimed at translating phrasal verbs in restricted syntactic domains has been created and released.

中文翻译：

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具有分布组合语义和单语语料库的短语动词的语境化翻译

本文描述了一种组合分布方法，以使用单语语料库生成语境化的词义并在目标语言中识别它们的适当翻译。单词翻译的建模方式与单词含义的上下文化相同，但在双语向量空间中。意义的上下文化是通过在具有句法依赖性的结构化向量空间内的分布式组合来实现的，而双语空间是通过转移规则和双语词典创建的。源语言中的短语由主语和从属语组成，通过选择给定主语的主语的最近邻和给定主语的从属语的最近邻来翻译成目标语言。这个过程通过增量组合扩展到更大的短语。在英语和西班牙语单语语料库上进行了实验，以便在上下文中翻译短语动词。已经创建并发布了一个新的双语数据集，用于评估旨在在受限句法域中翻译短语动词的策略。