@inProceedings{
 title = {Semantic role labeling via integer linear programming inference},
 type = {inProceedings},
 year = {2004},
 identifiers = {[object Object]},
 pages = {1346-es},
 volume = {3},
 issue = {1},
 websites = {http://portal.acm.org/citation.cfm?doid=1220355.1220552},
 publisher = {Association for Computational Linguistics},
 city = {Morristown, NJ, USA},
 id = {5468d409-7d54-3659-8632-e5d5889cc9e3},
 created = {2012-04-01T16:32:49.000Z},
 accessed = {2012-03-28},
 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 = {semantic role labeling},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Punyakanok2004},
 private_publication = {false},
 abstract = {We present a system for the semantic role la- beling task. The system combines a machine learning technique with an inference procedure based on integer linear programming that sup- ports the incorporation of linguistic and struc- tural constraints into the decision process. The system is tested on the data provided in the CoNLL-2004 shared task on semantic role la- beling and achieves very competitive results.},
 bibtype = {inProceedings},
 author = {Punyakanok, Vasin and Roth, Dan and Yih, Wen-tau and Zimak, Dav},
 booktitle = {Proceedings of the 20th international conference on Computational Linguistics - COLING '04}
}

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