Pivot Approach for Extracting Paraphrase Patterns from Bilingual Corpora

Proceedings of ACL-08: HLT, pages 780–788, Columbus, Ohio, USA, June 2008. c⃝2008 Association for Computational Linguistics Pivot Approach for Extracting Paraphrase Patterns from Bilingual Corpora Shiqi Zhao1, Haifeng Wang2, Ting Liu1, Sheng Li1 1Harbin Institute of Technology, Harbin, China {zhaosq,tliu,lisheng}@ir.hit.edu.cn 2Toshiba (China) Research and Development Center, Beijing, China wanghaifeng@rdc.toshiba.com.cn Abstract Paraphrase patterns are useful in paraphrase recognition and generation. In this paper, we present a pivot approach for extracting para- phrase patterns from bilingual parallel cor- pora, whereby the English paraphrase patterns are extracted using the sentences in a for- eign language as pivots. We propose a log- linear model to compute the paraphrase likeli- hood of two patterns and exploit feature func- tions based on maximum likelihood estima- tion (MLE) and lexical weighting (LW). Us- ing the presented method, we extract over 1,000,000 pairs of paraphrase patterns from 2M bilingual sentence pairs, the precision of which exceeds 67%. The evaluation re- sults show that: (1) The pivot approach is effective in extracting paraphrase patterns, which significantly outperforms the conven- tional method DIRT. Especially, the log-linear model with the proposed feature functions achieves high performance. (2) The coverage of the extracted paraphrase patterns is high, which is above 84%. (3) The extracted para- phrase patterns can be classified into 5 types, which are useful in various applications. 1 Introduction Paraphrases are different expressions that convey the same meaning. Paraphrases are important in plenty of natural language processing (NLP) ap- plications, such as question answering (QA) (Lin and Pantel, 2001; Ravichandran and Hovy, 2002), machine translation (MT) (Kauchak and Barzilay, 2006; Callison-Burch et al., 2006), multi-document summarization (McKeown et al., 2002), and natural language generation (Iordanskaja et al., 1991). Paraphrase patterns are sets of semantically equivalent patterns, in which a pattern generally contains two parts, i.e., the pattern words and slots. For example, in the pattern “X solves Y”, “solves” is the pattern word, while “X” and “Y” are slots. One can generate a text unit (phrase or sentence) by fill- ing the pattern slots with specific words. Paraphrase patterns are useful in both paraphrase recognition and generation. In paraphrase recognition, if two text units match a pair of paraphrase patterns and the corresponding slot-fillers are identical, they can be identified as paraphrases. In paraphrase generation, a text unit that matches a pattern P can be rewritten using the paraphrase patterns of P. A variety of methods have been proposed on para- phrase patterns extraction (Lin and Pantel, 2001; Ravichandran and Hovy, 2002; Shinyama et al., 2002; Barzilay and Lee, 2003; Ibrahim et al., 2003; Pang et al., 2003; Szpektor et al., 2004). However, these methods have some shortcomings. Especially, the precisions of the paraphrase patterns extracted with these methods are relatively low. In this paper, we extract paraphrase patterns from bilingual parallel corpora based on a pivot approach. We assume that if two English patterns are aligned with the same pattern in another language, they are likely to be paraphrase patterns. This assumption is an extension of the one presented …

Content truncated to 500 words