@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},
 file_attached = {false},
 profile_id = {5284e6aa-156c-3ce5-bc0e-b80cf09f3ef6},
 group_id = {066b42c8-f712-3fc3-abb2-225c158d2704},
 last_modified = {2017-03-14T14:36:19.698Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Romano2006},
 private_publication = {false},
 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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