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Effective bilingual constraints for semisupervised learning of named entity recognizers
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In: http://www.cs.stanford.edu/people/mengqiu/publication/aaai13.pdf (2013)
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Improving semantic role labeling with word sense
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In: http://www.aclweb.org/anthology-new/N/N10/N10-1030.pdf (2010)
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Multilingual Dependency-based Syntactic and Semantic Parsing
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In: http://ufal.mff.cuni.cz/conll2009-st/papers/15_conll09st.pdf (2009)
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Multilingual dependency-based syntactic and semantic parsing
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In: http://www.mt-archive.info/CoNLL-2009-Che.pdf (2009)
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Using a Hybrid Convolution Tree Kernel for Semantic Role Labeling
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In: http://ir.hit.edu.cn/~car/papers/talip.pdf (2008)
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Semantic role labeling using a grammar-driven convolution tree kernel. IEEE transactions on audio, speech, and language processing 16(7):1315
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In: http://ir.hit.edu.cn/ir_papers/2008/Semantic Role Labeling Using a Grammar-Driven Convolution Tree Kernel.pdf (2008)
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Type-Supervised Domain Adaptation for Joint Segmentation and POS-Tagging
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In: http://aclweb.org/anthology/E/E14/E14-1062.pdf
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Joint Optimization for Chinese POS Tagging and Dependency Parsing
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In: http://ir.hit.edu.cn/~car/papers/ieee14.pdf
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Micro blogs Oriented Word Segmentation System
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In: http://www.aclweb.org/anthology/W/W12/W12-6316.pdf
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HIT-IR-WSD: A WSD System for English Lexical Sample Task
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In: http://acl.ldc.upenn.edu/w/w07/W07-2034.pdf
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Using a Hybrid Convolution Tree Kernel for Semantic Role Labeling
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In: http://www.comp.nus.edu.sg/~tancl/Papers/TALIP/TALIP-Che.pdf
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Multilingual Dependency-based Syntactic and Semantic Parsing
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In: http://aclweb.org/anthology-new/W/W09/W09-1207.pdf
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Using Word Sense Disambiguation for Semantic Role Labeling
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In: http://ir.hit.edu.cn/~car/papers/iucs10.pdf
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Stacking Heterogeneous Joint Models of Chinese POS Tagging and Dependency Parsing
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In: http://ir.hit.edu.cn/~car/papers/coling12-joint.pdf
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Abstract:
Previous joint models of Chinese part-of-speech (POS) tagging and dependency parsing are extended from either graph- or transition-based dependency models. Our analysis shows that the two models have different error distributions. In addition, integration of graph- and transition-based dependency parsers by stacked learning (stacking) has achieved significant improvements. These motivate us to study the problem of stacking graph- and transition-based joint models. We conduct experiments on Chinese Penn Treebank 5.1 (CTB5.1). The results demonstrate that the guided transition-based joint model obtains better performance than the guided graph-based joint model. Further, we introduce a constituent-based joint model which derives the POS tag sequence and dependency tree from the output of PCFG parsers, and then integrate it into the guided transition-based joint model. Finally, we achieve the best performance on CTB5.1, 94.95 % in tagging accuracy and 83.98 % in parsing accuracy respectively.
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.410.295 http://ir.hit.edu.cn/~car/papers/coling12-joint.pdf
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A Cascaded Syntactic and Semantic Dependency Parsing System
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In: http://www.cnts.ua.ac.be/conll2008/pdf/23842.pdf
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Stacking Heterogeneous Joint Models of Chinese POS Tagging and Dependency Parsing
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In: http://aclweb.org/anthology/C/C12/C12-1188.pdf
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A Grammar-driven Convolution Tree Kernel for Semantic Role Classification
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In: http://acl.ldc.upenn.edu/p/p07/p07-1026.pdf
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HIT-CIR: An Unsupervised WSD System Based on Domain Most Frequent Sense Estimation
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In: http://aclweb.org/anthology/S/S10/S10-1091.pdf
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Joint Word Alignment and Bilingual Named Entity Recognition Using Dual Decomposition
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In: http://aclweb.org/anthology/P/P13/P13-1106.pdf
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A Grammar-driven Convolution Tree Kernel for Semantic Role Classification
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In: http://www.comp.nus.edu.sg/~tancl/Papers/ACL07/185.pdf
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