{"_id":"ax8EyJakMukRaJQzS","bibbaseid":"yoshikawa-riedel-hirao-asahara-matsumoto-coreferencebasedeventargumentrelationextractiononbiomedicaltext-2010","authorIDs":[],"author_short":["Yoshikawa, K.","Riedel, S.","Hirao, T.","Asahara, M.","Matsumoto, Y."],"bibdata":{"title":"Coreference Based Event-Argument Relation Extraction on Biomedical Text","type":"inProceedings","year":"2010","pages":"1-15","websites":"http://cl.naist.jp/~katsumasa-y/publications/smbm10.pdf","id":"109bf1f7-b506-3dd7-bc9e-8cbe503bc763","created":"2011-12-29T19:53:53.000Z","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","tags":"coreference resolution,relation extraction","read":false,"starred":false,"authored":false,"confirmed":"true","hidden":false,"citation_key":"Yoshikawa2010","private_publication":false,"abstract":"This paper presents a new approach that exploits coreference information to extract event-argument (E-A) relations from biomedical documents. This approach has two advantages: (1) it can extract a large number of valuable E-A relations based on the concept of salience in discourse (Grosz et al., 1995) ; (2) it enables us to iden- tify E-A relations over sentence bound- aries (cross-links) using transitivity involv- ing coreference relations. We propose two coreference-based models: a pipeline based on Support Vector Machine (SVM) classifiers, and a joint Markov Logic Net- work (MLN).We show the effectiveness of these models on a biomedical event corpus. The both models outperform the systems without coreference information. When compared with the two models, joint MLN outperforms pipeline SVM with gold coref- erence information.","bibtype":"inProceedings","author":"Yoshikawa, Katsumasa and Riedel, Sebastian and Hirao, Tsutomu and Asahara, Masayuki and Matsumoto, Yuji","booktitle":"Proceedings of the Fourth Symposium on Semantic Mining in Biomedicine SMBM 2010","bibtex":"@inProceedings{\n title = {Coreference Based Event-Argument Relation Extraction on Biomedical Text},\n type = {inProceedings},\n year = {2010},\n pages = {1-15},\n websites = {http://cl.naist.jp/~katsumasa-y/publications/smbm10.pdf},\n id = {109bf1f7-b506-3dd7-bc9e-8cbe503bc763},\n created = {2011-12-29T19:53:53.000Z},\n file_attached = {false},\n profile_id = {5284e6aa-156c-3ce5-bc0e-b80cf09f3ef6},\n group_id = {066b42c8-f712-3fc3-abb2-225c158d2704},\n last_modified = {2017-03-14T14:36:19.698Z},\n tags = {coreference resolution,relation extraction},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Yoshikawa2010},\n private_publication = {false},\n abstract = {This paper presents a new approach that exploits coreference information to extract event-argument (E-A) relations from biomedical documents. This approach has two advantages: (1) it can extract a large number of valuable E-A relations based on the concept of salience in discourse (Grosz et al., 1995) ; (2) it enables us to iden- tify E-A relations over sentence bound- aries (cross-links) using transitivity involv- ing coreference relations. We propose two coreference-based models: a pipeline based on Support Vector Machine (SVM) classifiers, and a joint Markov Logic Net- work (MLN).We show the effectiveness of these models on a biomedical event corpus. The both models outperform the systems without coreference information. When compared with the two models, joint MLN outperforms pipeline SVM with gold coref- erence information.},\n bibtype = {inProceedings},\n author = {Yoshikawa, Katsumasa and Riedel, Sebastian and Hirao, Tsutomu and Asahara, Masayuki and Matsumoto, Yuji},\n booktitle = {Proceedings of the Fourth Symposium on Semantic Mining in Biomedicine SMBM 2010}\n}","author_short":["Yoshikawa, K.","Riedel, S.","Hirao, T.","Asahara, M.","Matsumoto, Y."],"urls":{"Website":"http://cl.naist.jp/~katsumasa-y/publications/smbm10.pdf"},"bibbaseid":"yoshikawa-riedel-hirao-asahara-matsumoto-coreferencebasedeventargumentrelationextractiononbiomedicaltext-2010","role":"author","downloads":0,"html":""},"bibtype":"inProceedings","creationDate":"2020-02-06T23:48:11.894Z","downloads":0,"keywords":[],"search_terms":["coreference","based","event","argument","relation","extraction","biomedical","text","yoshikawa","riedel","hirao","asahara","matsumoto"],"title":"Coreference Based Event-Argument Relation Extraction on Biomedical Text","year":2010}