@inProceedings{
 title = {Preemptive information extraction using unrestricted relation discovery},
 type = {inProceedings},
 year = {2006},
 identifiers = {[object Object]},
 pages = {304-311},
 issue = {June},
 websites = {http://portal.acm.org/citation.cfm?doid=1220835.1220874},
 publisher = {Association for Computational Linguistics},
 id = {c1e43eee-83c9-3f0d-9cd6-6223c9f97f17},
 created = {2010-11-06T02:48:29.000Z},
 file_attached = {true},
 profile_id = {5284e6aa-156c-3ce5-bc0e-b80cf09f3ef6},
 group_id = {066b42c8-f712-3fc3-abb2-225c158d2704},
 last_modified = {2017-03-14T14:36:19.698Z},
 tags = {relation extraction},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Shinyama2006},
 private_publication = {false},
 abstract = {We are trying to extend the boundary of Information Extraction (IE) systems. Existing IE systems require a lot of time and human effort to tune for a new scenario. Preemptive Information Extraction is an attempt to automatically create all feasible IE systems in advance without human intervention. We propose a technique called Unrestricted Relation Discovery that discovers all possible relations from texts and presents them as tables. We present a preliminary system that obtains reasonably good results.},
 bibtype = {inProceedings},
 author = {Shinyama, Yusuke and Sekine, Satoshi},
 booktitle = {Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics}
}

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