Extracting Paraphrases from Definition Sentences on the Web

Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, pages 1087–1097, Portland, Oregon, June 19-24, 2011. c⃝2011 Association for Computational Linguistics Extracting Paraphrases from Definition Sentences on the Web Chikara Hashimoto∗ Kentaro Torisawa† Stijn De Saeger‡ Jun’ichi Kazama§ Sadao Kurohashi¶ ∗ † ‡ § National Institute of Information and Communications Technology Kyoto, 619-0237, JAPAN ∗ ¶Graduate School of Informatics, Kyoto University Kyoto, 606-8501, JAPAN {∗ ch,† torisawa, ‡ stijn,§ kazama}@nict.go.jp ¶ kuro@i.kyoto-u.ac.jp Abstract We propose an automatic method of extracting paraphrases from definition sentences, which are also automatically acquired from the Web. We observe that a huge number of concepts are defined in Web documents, and that the sentences that define the same concept tend to convey mostly the same information using different expressions and thus contain many paraphrases. We show that a large number of paraphrases can be automatically extracted with high precision by regarding the sentences that define the same concept as parallel cor- pora. Experimental results indicated that with our method it was possible to extract about 300,000 paraphrases from 6 × 108 Web docu- ments with a precision rate of about 94%. 1 Introduction Natural language allows us to express the same in- formation in many ways, which makes natural lan- guage processing (NLP) a challenging area. Ac- cordingly, many researchers have recognized that automatic paraphrasing is an indispensable compo- nent of intelligent NLP systems (Iordanskaja et al., 1991; McKeown et al., 2002; Lin and Pantel, 2001; Ravichandran and Hovy, 2002; Kauchak and Barzi- lay, 2006; Callison-Burch et al., 2006) and have tried to acquire a large amount of paraphrase knowledge, which is a key to achieving robust automatic para- phrasing, from corpora (Lin and Pantel, 2001; Barzi- lay and McKeown, 2001; Shinyama et al., 2002; Barzilay and Lee, 2003). We propose a method to extract phrasal para- phrases from pairs of sentences that define the same concept. The method is based on our observation that two sentences defining the same concept can be regarded as a parallel corpus since they largely convey the same information using different expres- sions. Such definition sentences abound on the Web. This suggests that we may be able to extract a large amount of phrasal paraphrase knowledge from the definition sentences on the Web. For instance, the following two sentences, both of which define the same concept “osteoporosis”, in- clude two pairs of phrasal paraphrases, which are indicated by underlines 1⃝ and 2⃝, respectively. (1) a. Osteoporosis is a disease that 1⃝ decreases the quantity of bone and 2⃝ makes bones fragile. b. Osteoporosis is a disease that 1⃝ reduces bone mass and 2⃝ increases the risk of bone fracture. We define paraphrase as a pair of expressions be- tween which entailment relations of both directions hold. (Androutsopoulos and Malakasiotis, 2010). Our objective is to extract phrasal paraphrases from pairs of sentences that define the same con- cept. We propose a supervised method that exploits various kinds of lexical similarity features and con- textual features. Sentences defining …

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