Paraphrasing with Bilingual Parallel Corpora

Proceedings of the 43rd Annual Meeting of the ACL, pages 597–604, Ann Arbor, June 2005. c⃝2005 Association for Computational Linguistics Paraphrasing with Bilingual Parallel Corpora Colin Bannard Chris Callison-Burch School of Informatics University of Edinburgh 2 Buccleuch Place Edinburgh, EH8 9LW {c.j.bannard, callison-burch}@ed.ac.uk Abstract Previous work has used monolingual par- allel corpora to extract and generate para- phrases. We show that this task can be done using bilingual parallel corpora, a much more commonly available resource. Using alignment techniques from phrase- based statistical machine translation, we show how paraphrases in one language can be identified using a phrase in another language as a pivot. We define a para- phrase probability that allows paraphrases extracted from a bilingual parallel corpus to be ranked using translation probabili- ties, and show how it can be refined to take contextual information into account. We evaluate our paraphrase extraction and ranking methods using a set of manual word alignments, and contrast the qual- ity with paraphrases extracted from auto- matic alignments. 1 Introduction Paraphrases are alternative ways of conveying the same information. Paraphrases are useful in a num- ber of NLP applications. In natural language gen- eration the production of paraphrases allows for the creation of more varied and fluent text (Iordanskaja et al., 1991). In multidocument summarization the identification of paraphrases allows information re- peated across documents to be condensed (McKe- own et al., 2002). In the automatic evaluation of machine translation, paraphrases may help to alle- viate problems presented by the fact that there are often alternative and equally valid ways of translat- ing a text (Pang et al., 2003). In question answering, discovering paraphrased answers may provide addi- tional evidence that an answer is correct (Ibrahim et al., 2003). In this paper we introduce a novel method for ex- tracting paraphrases that uses bilingual parallel cor- pora. Past work (Barzilay and McKeown, 2001; Barzilay and Lee, 2003; Pang et al., 2003; Ibrahim et al., 2003) has examined the use of monolingual par- allel corpora for paraphrase extraction. Examples of monolingual parallel corpora that have been used are multiple translations of classical French novels into English, and data created for machine transla- tion evaluation methods such as Bleu (Papineni et al., 2002) which use multiple reference translations. While the results reported for these methods are impressive, their usefulness is limited by the scarcity of monolingual parallel corpora. Small data sets mean a limited number of paraphrases can be ex- tracted. Furthermore, the narrow range of text gen- res available for monolingual parallel corpora limits the range of contexts in which the paraphrases can be used. Instead of relying on scarce monolingual parallel data, our method utilizes the abundance of bilingual parallel data that is available. This allows us to cre- ate a much larger inventory of phrases that is appli- cable to a wider range of texts. Our method for identifying paraphrases is an extension of recent work in phrase-based statisti- cal machine translation (Koehn et al., 2003). The essence of our method …

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