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Enlarging paraphrase collections through generalization and instantiation

 
 
Affiliation:
Information and Communication Technologies; National Research Council Canada
Language:
English
Type:
Conference publication
Conference:
Joint Conference on Empirical Methods on Natural Language Processing and Computational Natural Language Learning (EMNLP-CONLL 2012), Jeju Island, Korea, July 12-14, 2012
Proceedings
Title:
Proceedings of the Joint Conference on Empirical Methods on Natural Language Processing and Computational Natural Language Learning
Date:
2012
Pages :
631-642
NPArC #:
20494942
Program(s):
Natural Language Processing; Traitement des langues naturelles
Group(s):
Interactive Language Technologies; Technologies langagières interactives
Abstract:
This paper presents a paraphrase acquisition method that uncovers and exploits generalities underlying paraphrases: paraphrase patterns are first induced and then used to collect novel instances. Unlike existing methods, ours uses both bilingual parallel and monolingual corpora. While the former are regarded as a source of high-quality seed paraphrases, the latter are searched for paraphrases that match patterns learned from the seed paraphrases. We show how one can use monolingual corpora, which are far more numerous and larger than bilingual corpora, to obtain paraphrases that rival in quality those derived directly from bilingual corpora. In our experiments, the number of paraphrase pairs obtained in this way from monolingual corpora was a large multiple of the number of seed paraphrases. Human evaluation through a paraphrase substitution test demonstrated that the newly acquired paraphrase pairs are of reasonable quality. Remaining noise can be further reduced by filtering seed paraphrases.
 
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