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We propose a novel deep learning model for joint document-level entity disambiguation, which leverages learned neural representations.
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Zhengyan He, Shujie Liu, Mu Li, Ming Zhou, Longkai Zhang, and Houfeng Wang. 2013 · 2013
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Yaming Sun, Lei Lin, Duyu Tang, Nan Yang, Zhenzhou Ji, and Xiaolong Wang. 2015 · 2015
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Entity disambiguation by knowledge and text jointly embedding
Wei Fang, Jianwen Zhang, Dilin Wang, Zheng Chen, and Ming Li. 2016 · 2016
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Capturing semantic similarity for entity linking with convolutional neural networks
Matthew Francis-Landau, Greg Durrett, and Dan Klein. 2016 · 2016
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Octavian-Eugen Ganea, Marina Ganea, Aurelien Lucchi, Carsten Eickhoff, and Thomas Hofmann. 2016 · 2016
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Glove: Global vectors for word representation
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Andrew Chisholm and Ben Hachey. 2015 · 2015
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Emily Denton, Jason Weston, Manohar Paluri, Lubomir Bourdev, and Rob Fergus. 2015 · 2015
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Leveraging deep neural networks and knowledge graphs for entity disambiguation
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Joint learning of the embedding of words and entities for named entity disambiguation
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