Investigating a Generic Paraphrase-based Approach for Relation Extraction. Romano, L.; Kouylekov, M.; Szpektor, I.; Dagan, I.; and Lavelli, A. EACL 2006 11th Conference of the European Chapter of the Association for Computational Linguistics, 2006.
Investigating a Generic Paraphrase-based Approach for Relation Extraction [link]Website  abstract   bibtex   
Unsupervised paraphrase acquisition has been an active research field in recent years, but its effective coverage and performance have rarely been evaluated. We propose a generic paraphrase-based approach for Relation Extraction (RE), aiming at a dual goal: obtaining an applicative evaluation scheme for paraphrase acquisition and obtaining a generic and largely unsupervised configuration for RE.We analyze the potential of our approach and evaluate an implemented prototype of it using an RE dataset. Our findings reveal a high potential for unsupervised paraphrase acquisition. We also identify the need for novel robust models for matching paraphrases in texts, which should address syntactic complexity and variability.
@article{
 title = {Investigating a Generic Paraphrase-based Approach for Relation Extraction},
 type = {article},
 year = {2006},
 keywords = {information retrieval & textual information access,natural language processing},
 pages = {409–416},
 websites = {http://eprints.pascal-network.org/archive/00002676/},
 id = {ae9a62ea-96fa-318d-9a39-1321ce5a0127},
 created = {2010-11-06T02:48:29.000Z},
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 abstract = {Unsupervised paraphrase acquisition has been an active research field in recent years, but its effective coverage and performance have rarely been evaluated. We propose a generic paraphrase-based approach for Relation Extraction (RE), aiming at a dual goal: obtaining an applicative evaluation scheme for paraphrase acquisition and obtaining a generic and largely unsupervised configuration for RE.We analyze the potential of our approach and evaluate an implemented prototype of it using an RE dataset. Our findings reveal a high potential for unsupervised paraphrase acquisition. We also identify the need for novel robust models for matching paraphrases in texts, which should address syntactic complexity and variability.},
 bibtype = {article},
 author = {Romano, Lorenza and Kouylekov, Milen and Szpektor, Idan and Dagan, Ido and Lavelli, Alberto},
 journal = {EACL 2006 11th Conference of the European Chapter of the Association for Computational Linguistics}
}
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