While paraphrasing is critical both for interpretation and generation of natural language, current systems use manual or semi-automatic methods to collect paraphrases. We present an unsupervised learning algorithm for identification of paraphrases from a corpus of multiple English translations of the same source text. Our approach yields phrasal and single word lexical paraphrases as well as syntactic paraphrases.
Work on paraphrase generation: REF extract paraphrases from a monolingual parallel corpus, containing multiple translations of the same source.
Extracting Paraphrases From A Parallel Corpus
Annual Meeting Of The Association For Computational Linguistics
Computer Science