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The Knowledge Graph Entity Typing (KGET) task aims to predict missing type annotations for entities in knowledge graphs.
Yago: A core of semantic knowledge
Fabian M. Suchanek, Gjergji Kasneci, and Gerhard Weikum. 2007 · 2007
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Freebase: A collaboratively created graph database for structuring human knowledge
Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor. 2008 · 2008
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Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Durán, Jason Weston, and Oksana Yakhnenko. 2013 · 2013
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Wikidata: A free collaborative knowledgebase
Denny Vrandečić and Markus Krötzsch. 2014 · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling. 2017 · 2017
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Learning entity type embeddings for knowledge graph completion
Changsung Moon, Paul Jones, and Nagiza F. Samatova. 2017b · 2017
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Modeling Relational Data with Graph Convolutional Networks , pages 593–607
Michael Schlichtkrull, Thomas Kipf, Peter Bloem, Rianne Berg, Ivan Titov, and Max Welling. 2018 · 2018
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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 · 2019
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Fine-grained entity typing via hierarchical multi graph convolutional networks
Hailong Jin, Lei Hou, Juanzi Li, and Tiansi Dong. 2019 · 2019
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Rotate: Knowledge graph embedding by relational rotation in complex space
Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, and Jian Tang. 2019 · 2019
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A relation extraction method based on entity type embedding and recurrent piecewise residual networks
Yuming Wang, Huiqiang Zhao, Lai Tu, Jingpei Dan, and Ling Liu. 2019 · 2019
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Improving entity linking by modeling latent entity type information
Shuang Chen, Jinpeng Wang, Feng Jiang, and Chin-Yew Lin. 2020 · 2020
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FastBERT: a self-distilling BERT with adaptive inference time
Weijie Liu, Peng Zhou, Zhiruo Wang, Zhe Zhao, Haotang Deng, and Qi Ju. 2020 · 2020
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Knowledge graph entity typing via learning connecting embeddings
Yu Zhao, Anxiang Zhang, Huali Feng, Qing Li, Patrick Gallinari, and Fuji Ren. 2020 · 2020
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Cat2type: Wikipedia category embeddings for entity typing in knowledge graphs
Russa Biswas, Radina Sofronova, Harald Sack, and Mehwish Alam. 2021 · 2021
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Transformer-based entity typing in knowledge graphs
Zhiwei Hu, Victor Gutierrez-Basulto, Zhiliang Xiang, Ru Li, and Jeff Pan. 2022a · 2022
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Empowering language models with knowledge graph reasoning for open-domain question answering
Ziniu Hu, Yichong Xu, Wenhao Yu, Shuohang Wang, Ziyi Yang, Chenguang Zhu, Kai-Wei Chang, and Yizhou Sun. 2022c · 2022
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A good neighbor, a found treasure: Mining treasured neighbors for knowledge graph entity typing
Zhuoran Jin, Pengfei Cao, Yubo Chen, Kang Liu, and Jun Zhao. 2022 · 2022
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Towards an optimal asymmetric graph structure for robust semi-supervised node classification
Zixing Song, Yifei Zhang, and Irwin King. 2022 · 2022
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RoBERTa-based traditional Chinese medicine named entity recognition model
Ming-Hsiang Su, Chin-Wei Lee, Chi-Lun Hsu, and Ruei-Cyuan Su. 2022 · 2022
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Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
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Robust knowledge graph completion with stacked convolutions and a student re-ranking network
Justin Lovelace, Denis Newman-Griffis, Shikhar Vashishth, Jill Fain Lehman, and Carolyn Rosé. 2021 · 2021
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Context-aware entity typing in knowledge graphs
Weiran Pan, Wei Wei, and Xian-Ling Mao. 2021 · 2021
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Semi-supervised multi-label learning for graph-structured data
Zixing Song, Ziqiao Meng, Yifei Zhang, and Irwin King. 2021 · 2021
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Residual attention: A simple but effective method for multi-label recognition
K. Zhu and J. Wu. 2021 · 2021
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Entity type prediction leveraging graph walks and entity descriptions
Russa Biswas, Jan Portisch, Heiko Paulheim, Harald Sack, and Mehwish Alam. 2022 · 2022
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Type-aware embeddings for multi-hop reasoning over knowledge graphs
Zhiwei Hu, Victor Gutierrez Basulto, Zhiliang Xiang, Xiaoli Li, Ru Li, and Jeff Z. Pan. 2022b
Cited in the paper.
SimKGC: Simple contrastive knowledge graph completion with pre-trained language models
Liang Wang, Wei Zhao, Zhuoyu Wei, and Jingming Liu. 2022 · 2022
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Connecting embeddings based on multiplex relational graph attention networks for knowledge graph entity typing
Yu Zhao, Han Zhou, Anxiang Zhang, Ruobing Xie, Qing Li, and Fuzhen Zhuang. 2022 · 2022
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A neighborhood-attention fine-grained entity typing for knowledge graph completion
Jianhuan Zhuo, Qiannan Zhu, Yinliang Yue, Yuhong Zhao, and Weisi Han. 2022 · 2022
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Knowledge graph entity type prediction with relational aggregation graph attention network
Changlong Zou, Jingmin An, and Guanyu Li. 2022 · 2022
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Compounding geometric operations for knowledge graph completion
Xiou Ge, Yun Cheng Wang, Bin Wang, and C.-C. Jay Kuo. 2023 · 2023
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Complex embeddings for simple link prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard. 2016 · 2080
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