@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} }