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1
Chinese Abstract Meaning Representation 2.0
Li, Bin; Xiao, Liming; Liu, Yihuan. - : Linguistic Data Consortium, 2021. : https://www.ldc.upenn.edu, 2021
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2
Factuality Assessment as Modal Dependency Parsing ...
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3
Chinese Abstract Meaning Representation 2.0 ...
Xiao, Liming; Liu, Yihuan; Li, Bin. - : Linguistic Data Consortium, 2021
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4
Chinese Abstract Meaning Representation 1.0
Li, Bin; Wen, Yuan; Song, Li. - : Linguistic Data Consortium, 2019. : https://www.ldc.upenn.edu, 2019
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5
Chinese Abstract Meaning Representation 1.0 ...
Li, Bin; Wen, Yuan; Song, Li. - : Linguistic Data Consortium, 2019
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6
GALE English-Chinese Parallel Aligned Treebank -- Training
Li, Xuansong; Grimes, Stephen; Strassel, Stephanie. - : Linguistic Data Consortium, 2017. : https://www.ldc.upenn.edu, 2017
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7
2015-2016 CoNLL Shared Task
Xue, Nianwen; Ng, Hwee Tou; Pradhan, Sameer. - : Linguistic Data Consortium, 2017. : https://www.ldc.upenn.edu, 2017
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8
Addressing the Data Sparsity Issue in Neural AMR Parsing ...
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9
2015-2016 CoNLL Shared Task ...
Xue, Nianwen; Ng, Hwee Tou; Pradhan, Sameer. - : Linguistic Data Consortium, 2017
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10
GALE English-Chinese Parallel Aligned Treebank -- Training ...
Li, Xuansong; Grimes, Stephen; Strassel, Stephanie. - : Linguistic Data Consortium, 2017
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11
Two layers of annotation for representing event mentions in news stories
Buono, Maria Pia di; Tutek, Martin; Šnajder, Jan. - : Association for Computational Linguistics, 2017
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12
Chinese Treebank 9.0
Xue, Nianwen; Zhang, Xiuhong; Jiang, Zixin. - : Linguistic Data Consortium, 2016. : https://www.ldc.upenn.edu, 2016
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13
Neural Network Models for Implicit Discourse Relation Classification in English and Chinese without Surface Features ...
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14
Chinese Treebank 9.0 ...
Xue, Nianwen; Zhang, Xiuhong; Jiang, Zixin. - : Linguistic Data Consortium, 2016
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15
A convolution BiLSTM neural network model for Chinese event extraction
Abstract: Chinese event extraction is a challenging task in information extraction. Previous approaches highly depend on sophisticated feature engineering and complicated natural language processing (NLP) tools. In this paper, we first come up with the language specific issue in Chinese event extraction, and then propose a convolution bidirectional LSTM neural network that combines LSTM and CNN to capture both sentence-level and lexical information without any hand-craft features. Experiments on ACE 2005 dataset show that our approaches can achieve competitive performances in both trigger labeling and argument role labeling.
URL: https://eprints.lancs.ac.uk/id/eprint/83783/1/160.pdf
https://eprints.lancs.ac.uk/id/eprint/83783/
https://doi.org/10.1007/978-3-319-50496-4_23
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16
GALE Chinese-English Parallel Aligned Treebank -- Training
Li, Xuansong; Grimes, Stephen; Strassel, Stephanie. - : Linguistic Data Consortium, 2015. : https://www.ldc.upenn.edu, 2015
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17
GALE Chinese-English Parallel Aligned Treebank -- Training ...
Li, Xuansong; Grimes, Stephen; Strassel, Stephanie. - : Linguistic Data Consortium, 2015
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18
Chinese Discourse Treebank 0.5
Zhou, Yuping; Lu, Jill; Zhang, Jennifer. - : Linguistic Data Consortium, 2014. : https://www.ldc.upenn.edu, 2014
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19
Chinese Discourse Treebank 0.5 ...
Lu, Jill; Zhang, Jennifer; Xue, Nianwen. - : Linguistic Data Consortium, 2014
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20
OntoNotes Release 5.0
Weischedel, Ralph; Palmer, Martha; Marcus, Mitchell. - : Linguistic Data Consortium, 2013. : https://www.ldc.upenn.edu, 2013
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