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Hybrid Simplification using Deep Semantics and Machine Translation

机译:使用深层语义和机器翻译混合简化

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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:我们介绍了一种混合方法,句子简化,将深度语义和单晶机器翻译结合到复杂的句子中的简单句子。这种方法与以前的工作不同于两种主要方式。首先,它是基于语义,因为它需要输入深度语义表示而不是例如句子或解析树。其次,它结合了一种简化模型来分割和删除与单语翻译模型进行短语替换和重新排序。与现有技术的当前状态进行比较时,我们的模型产生了显着更简单的输出,这既具有语法和意义保留。

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