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Academic Paper


Title: Extracting paraphrase patterns from bilingual parallel corpora
Author: Shiqi Zhao
Institution: Harbin Institute of Technology
Author: Haifeng Wang
Institution: Baidu
Author: Ting Liu
Institution: Harbin Institute of Technology
Author: Sheng Li
Institution: Harbin Institute of Technology
Linguistic Field: Morphology; Semantics
Abstract: Paraphrase patterns are semantically equivalent patterns, which are useful in both paraphrase recognition and generation. This paper presents a pivot approach for extracting paraphrase patterns from bilingual parallel corpora, whereby the paraphrase patterns in English are extracted using the patterns in another language as pivots. We make use of log-linear models for computing the paraphrase likelihood between pattern pairs and exploit feature functions based on maximum likelihood estimation (MLE), lexical weighting (LW), and monolingual word alignment (MWA). Using the presented method, we extract more than 1 million pairs of paraphrase patterns from about 2 million pairs of bilingual parallel sentences. The precision of the extracted paraphrase patterns is above 78%. Experimental results show that the presented method significantly outperforms a well-known method called discovery of inference rules from text (DIRT). Additionally, the log-linear model with the proposed feature functions are effective. The extracted paraphrase patterns are fully analyzed. Especially, we found that the extracted paraphrase patterns can be classified into five types, which are useful in multiple natural language processing (NLP) applications.

CUP AT LINGUIST

This article appears IN Natural Language Engineering Vol. 15, Issue 4, which you can READ on Cambridge's site or on LINGUIST .



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