Learning Sentential Paraphrases from Bilingual Parallel Corpora for Text-to-Text Generation
Juri Ganitkevitch, Chris Callison-Burch, Courtney Napoles, Benjamin Van Durme · 2011
Previous work has shown that high quality phrasal paraphrases can be extracted from bilingual parallel corpora. However, it is not clear whether bitexts are an appropriate resource for extracting more sophisticated sentential paraphrases, which are more obviously learnable from monolingual parallel corpora. We extend bilingual paraphrase extraction to syntactic paraphrases and demonstrate its ability to learn a variety of general paraphrastic transformations, including passivization, dative shift, topicalization, etc. We discuss how our model can be adapted to many text generation tasks, by augmenting its feature set, development data and parameter estimation routine. We illustrate this adaptation by using our paraphrase model for the task of sentence compression and achieve results that improve on state-of-the-art compression systems. 1