2008b. Pivot approach for extracting paraphrase patterns from bilingual corpora

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.