Sentence compression with natural language generation

Abstract

We present a novel unsupervised method for sentence compression which relies on a Stanford Typed Dependencies to extract information items, then generates compressed sentences via Natural Language Generation(NLG) engine. An automatic evaluation shows that our method obtains better results. We demonstrate that the choice of the parser affects the performance of the system. © 2011 Springer-Verlag Berlin Heidelberg.