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2008b. Pivot Approach for Extracting Paraphrase Patterns from Bilingual Corpora
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| Venue: | In Proceedings of ACL-08:HLT |
| Citations: | 24 - 3 self |
BibTeX
@INPROCEEDINGS{Zhao_2008b.pivot,
author = {Shiqi Zhao and Haifeng Wang and Ting Liu and Sheng Li},
title = {2008b. Pivot Approach for Extracting Paraphrase Patterns from Bilingual Corpora},
booktitle = {In Proceedings of ACL-08:HLT},
year = {},
pages = {780--788}
}
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Abstract
Paraphrase patterns are useful in paraphrase recognition and generation. In this paper, we present a pivot approach for extracting paraphrase patterns from bilingual parallel corpora, whereby the English paraphrase patterns are extracted using the sentences in a foreign language as pivots. We propose a loglinear model to compute the paraphrase likelihood of two patterns and exploit feature functions based on maximum likelihood estimation (MLE) and lexical weighting (LW). Using 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 results show that: (1) The pivot approach is effective in extracting paraphrase patterns, which significantly outperforms the conventional 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 paraphrase patterns can be classified into 5 types, which are useful in various applications. 1
Keyphrases
pivot approach paraphrase pattern extracting paraphrase pattern bilingual corpus extracted paraphrase pattern maximum likelihood estimation lexical weighting paraphrase likelihood log-linear model various application exploit feature function feature function high performance evaluation result loglinear model foreign language conventional method dirt bilingual sentence pair paraphrase recognition english paraphrase pattern bilingual parallel corpus
