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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 20 of 20 1 The importance of syntactic parsing and inference in semantic role labeling Vasin Punyakanok; Dan Roth; Wen-tau Yih In: http://l2r.cs.uiuc.edu/~danr/Papers/PunyakanokRoYi07.pdf (2008) BASE Show details 2 The importance of syntactic parsing and inference in semantic role labeling Vasin Punyakanok; Dan Roth In: http://wing.comp.nus.edu.sg/~antho/J/J08/J08-2005.pdf (2008) BASE Show details 3 An Exploratory Study Towards ‘Machines that Learn to Read Elizabeth Boschee; Vasin Punyakanok; Ralph Weischedel In: http://www.aaai.org/Papers/Symposia/Fall/2008/FS-08-04/FS08-04-007.pdf (2008) BASE Show details 4 Natural language inference via dependency tree mapping: An application to question answering Vasin Punyakanok; Dan Roth; Wen-tau Yih In: http://l2r.cs.uiuc.edu/~danr/Papers/PunyakanokRoYi04.pdf (2004) BASE Show details 5 Semantic role labeling via integer linear programming inference Vasin Punyakanok; Dan Roth; Wen-tau Yih... In: http://l2r.cs.uiuc.edu/~danr/Papers/PRYZ04.pdf (2004) BASE Show details 6 Semantic role labeling via integer linear programming inference Vasin Punyakanok; Dan Roth; Wen-tau Yih... In: http://newdesign.aclweb.org/anthology-new/C/C04/C04-1197.pdf (2004) BASE Show details 7 Semantic role labeling via generalized inference over classifiers Vasin Punyakanok; Dan Roth; Wen-tau Yih... In: http://l2r.cs.uiuc.edu/~danr/Papers/PRYZT04.pdf (2004) BASE Show details 8 Applying System Combination to Base Noun Phrase Identification Erik F. Tjong; Kim Sang; Walter Daelemans... In: http://lcg-www.uia.ac.be/~erikt/papers/coling2000.ps.gz (2000) BASE Show details 9 Applying System Combination to Base Noun Phrase Identification Erik k F. Tjong Kim Sang; Walter Daelemans; Hervé Déjean... In: http://nlp3.korea.ac.kr/proceeding/coling2000/COLING/pdf/124.pdf (2000) BASE Show details 10 Proceedings Th International Conference; Erik F. Tjong; Kim Sang... In: http://cnts.uia.ac.be/~walter/papers/2000/sddkkpr00.ps (2000) BASE Show details 11 Erik F. Tjong Kim Sang Walter Daelemans Herv'e; Erik F. Tjong; Kim Sang... In: http://nlp3.korea.ac.kr/proceeding/coling2000/COLING/ps/124.ps (2000) BASE Show details 12 Applying System Combination to Base Noun Phrase Identification Erik F. Tjong Kim Sang; Walter Daelemans; Hervé Déjean... In: http://l2r.cs.uiuc.edu/~danr/Papers/coling00.ps.gz (2000) BASE Show details 13 Applying System Combination to Base Noun Phrase Identification Erik F. Tjong Kim Sang; Walter Daelemans; Hervé Déjean T... In: http://acl.ldc.upenn.edu/C/C00/C00-2124.pdf (2000) BASE Show details 14 A Learning Approach to Shallow Parsing Marcia Muñoz; Vasin Punyakanok; Dan Roth... In: http://l2r.cs.uiuc.edu/~danr/Papers/emnlp99.ps.gz (1999) BASE Show details 15 A Learning Approach to Shallow Parsing Marcia Muñoz; Vasin Punyakanok; Dan Roth; Dav Zimak In: http://l2r.cs.uiuc.edu/~danr/Papers/shallow-long.ps.gz (1999) Abstract: A SNoW based learning approach to shallow parsing tasks is presented and studied experimentally. The shallow parsing method suggested learns to identify syntactic patterns by combining simple predictors to produce a coherent inference. Learned predictors are cascaded and their outcome is used as an input to an inference algorithm that produces the nal phrases. We discuss the requirements from a learning system for this approach to be applicable and present a system based on the SNoW learning architecture that satises these conditions. Two instantiations of this approach are studied and experimental results for Noun-Phrases (NP) and Subject-Verb (SV) phrases that compare favorably with the best published results are presented. In doing that, we compare two ways of modeling the problem of learning to recognize patterns and suggest that shallow parsing patterns are better learned using open/close predictors than using inside/outside predictors. 1 Introduction Shallow parsing. URL: http://l2r.cs.uiuc.edu/~danr/Papers/shallow-long.ps.gz http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.46.7655 BASE Hide details 16 A learning approach to shallow parsing Marcia Muñoz; Vasin Punyakanok; Dan Roth... In: http://www.ceng.metu.edu.tr/courses/ceng463/20032/project/Guzen/shallow parsing.pdf (1999) BASE Show details 17 A Learning Approach to Shallow Parsing Marcia Muñoz; Vasin Punyakanok; Dan Roth... In: http://www.students.uiuc.edu/~mmunoz/shallow.ps (1999) BASE Show details 18 A Learning Approach to Shallow Parsing Marcia Muñoz; Vasin Punyakanok; Dan Roth... In: http://www.students.uiuc.edu/~mmunoz/emnlp99.ps (1999) BASE Show details 19 A Learning Approach to Shallow Parsing Marcia Muñoz; Vasin Punyakanok; Dan Roth... In: http://acl.ldc.upenn.edu/W/W99/W99-0621.pdf (1999) BASE Show details 20 COLING ’04 Semantic Role Labeling via Integer Linear Programming Inference Vasin Punyakanok; Dan Roth; Wen-tau Yih... In: http://cogcomp.cs.illinois.edu/sites/LX/coling04.pdf BASE Show details

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