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Hybrid Simplification using Deep Semantics and Machine Translation

机译:使用深度语义和机器翻译的混合简化

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We present a hybrid approach to sentence simplification which combines deep semantics and monolingual machine translation to derive simple sentences from complex ones. The approach differs from previous work in two main ways. First, it is semantic based in that it takes as input a deep semantic representation rather than e.g., a sentence or a parse tree. Second, it combines a simplification model for splitting and deletion with a monolingual translation model for phrase substitution and reordering. When compared against current state of the art methods, our model yields significantly simpler output that is both grammatical and meaning preserving.
机译:我们提出了一种简化句子的混合方法,该方法结合了深层语义和单语机器翻译,可以从复杂的句子中提取出简单的句子。该方法与以前的工作有两个主要方面的不同。首先,它是基于语义的,因为它将深度的语义表示而不是例如句子或语法分析树作为输入。其次,它结合了用于拆分和删除的简化模型以及用于短语替换和重新排序的单语翻译模型。与当前的最新方法进行比较时,我们的模型产生的语法和含义都非常简单。

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