Sentence splitting is a major simplification operator. Here we present a
simple and efficient splitting algorithm based on an automatic semantic parser.
After splitting, the text is amenable for further fine-tuned simplification
operations. In particular, we show that neural Machine Translation can be
effectively used in this situation. Previous application of Machine Translation
for simplification suffers from a considerable disadvantage in that they are
over-conservative, often failing to modify the source in any way. Splitting
based on semantic parsing, as proposed here, alleviates this issue. Extensive
automatic and human evaluation shows that the proposed method compares
favorably to the state-of-the-art in combined lexical and structural
simplification.

本论文提出了一种基于自动语义分析器的简单有效的句子分割算法，并通过神经机器翻译进行进一步微调的简化操作，其中采用语义分析为基础的分割方式可以有效地解决以往机器翻译的过于保守的问题，经过广泛的自动化和人工评估，该方法在词汇和结构简化方面表现优异。