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In natural language processing, relation extraction seeks to rationally understand unstructured text.
Kernel methods for relation extraction
Dmitry Zelenko, Chinatsu Aone, and Anthony Richardella · 2003
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A shortest path dependency kernel for relation extraction
Razvan C. Bunescu and Raymond J. Mooney · 2005
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Simple algorithms for complex relation extraction with applications to biomedical ie
Ryan McDonald, Fernando Pereira, Seth Kulick, Scott Winters, Yang Jin, and Pete White · 2005
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Distant supervision for relation extraction without labeled data
Mike Mintz, Steven Bills, Rion Snow, and Dan Jurafsky · 2009
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Knowledge base population: Successful approaches and challenges
Heng Ji and Ralph Grishman · 2011
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Identifying relations for open information extraction
Anthony Fader, Stephen Soderland, and Oren Etzioni · 2011
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Parsing with compositional vector grammars
Richard Socher, John Bauer, Christopher D Manning, and Andrew Y Ng · 2013
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Relation classification via convolutional deep neural network
Daojian Zeng, Kang Liu, Siwei Lai, Guangyou Zhou, Jun Zhao, et al · 2014
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A dependency-based neural network for relation classification
Yang Liu, Furu Wei, Sujian Li, Heng Ji, Ming Zhou, and Houfeng Wang · 2015
Cited alongside, same era.
Classifying relations via long short term memory networks along shortest dependency paths
Yan Xu, Lili Mou, Ge Li, Yunchuan Chen, Hao Peng, and Zhi Jin · 2015
Cited alongside, same era.
Relation classification via multi-level attention cnns
Linlin Wang, Zhu Cao, Gerard De Melo, and Zhiyuan Liu · 2016
Cited alongside, same era.
Attention-based bidirectional long short-term memory networks for relation classification
Peng Zhou, Wei Shi, Jun Tian, Zhenyu Qi, Bingchen Li, Hongwei Hao, and Bo Xu · 2016
Cited alongside, same era.
Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling · 2016
Cited alongside, same era.
Position-aware attention and supervised data improve slot filling
Yuhao Zhang, Victor Zhong, Danqi Chen, Gabor Angeli, and Christopher D Manning · 2017
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Graph convolution over pruned dependency trees improves relation extraction
Yuhao Zhang, Peng Qi, and Christopher D Manning · 2018
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Spanbert: Improving pre-training by representing and predicting spans
Mandar Joshi, Danqi Chen, Yinhan Liu, Daniel S Weld, Luke Zettlemoyer, and Omer Levy · 2019
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Enriching pre-trained language model with entity information for relation classification
Shanchan Wu and Yifan He · 2019
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Matching the blanks: Distributional similarity for relation learning
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Improved neural relation detection for knowledge base question answering
Mo Yu, Wenpeng Yin, Kazi Saidul Hasan, Cicero dos Santos, Bing Xiang, and Bowen Zhou · 2017
Cited alongside, same era.
Cross-sentence n-ary relation extraction with graph lstms
Nanyun Peng, Hoifung Poon, Chris Quirk, Kristina Toutanova, and Wen-tau Yih · 2017
Cited alongside, same era.
Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling, and Tom Kwiatkowski · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Simple bert models for relation extraction and semantic role labeling
Peng Shi and Jimmy Lin · 2019
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