Fetching the paper…
Reading the bibliography…
We propose yet another entity linking model (YELM) which links words to entities instead of spans.
Pre-training of deep contextualized embeddings of words and entities for named entity disambiguation
Ikuya Yamada and Hiroyuki Shindo. 2019 · 1909
Earlier work this paper cites.
Bert is not a knowledge base (yet): Factual knowledge vs. name-based reasoning in unsupervised qa
Nina Poerner, Ulli Waltinger, and Hinrich Schütze. 2019 · 1911
Earlier work this paper cites.
Text chunking using transformation-based learning
Lance Ramshaw and Mitch Marcus. 1995 · 1995
Earlier work this paper cites.
Yago: A Core of Semantic Knowledge
Fabian M. Suchanek, Gjergji Kasneci, and Gerhard Weikum. 2007 · 2007
Earlier work this paper cites.
Robust disambiguation of named entities in text
Johannes Hoffart, Mohamed Amir Yosef, Ilaria Bordino, Hagen Fürstenau, Manfred Pinkal, Marc Spaniol, Bilyana Taneva, Stefan Thater, and Gerhard Weikum. 2011 · 2011
Earlier work this paper cites.
Local and global algorithms for disambiguation to wikipedia
Lev Ratinov, Dan Roth, Doug Downey, and Mike Anderson. 2011 · 2011
Earlier work this paper cites.
Re-ranking for joint named-entity recognition and linking
Avirup Sil and Alexander Yates. 2013 · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
Transition-based dependency parsing with stack long short-term memory
Chris Dyer, Miguel Ballesteros, Wang Ling, Austin Matthews, and Noah A. Smith. 2015 · 2015
Earlier work this paper cites.
Joint entity recognition and disambiguation
Gang Luo, Xiaojiang Huang, Chin-Yew Lin, and Zaiqing Nie. 2015 · 2015
Earlier work this paper cites.
Collective entity resolution with multi-focal attention
Amir Globerson, Nevena Lazic, Soumen Chakrabarti, Amarnag Subramanya, Michael Ringaard, and Fernando Pereira. 2016 · 2016
Earlier work this paper cites.
J-nerd: joint named entity recognition and disambiguation with rich linguistic features
Dat Ba Nguyen, Martin Theobald, and Gerhard Weikum. 2016 · 2016
Cited alongside, same era.
Joint learning of the embedding of words and entities for named entity disambiguation
Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda, and Yoshiyasu Takefuji. 2016 · 2016
Cited alongside, same era.
Enriching word vectors with subword information
Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2017 · 2017
Cited alongside, same era.
Bridge text and knowledge by learning multi-prototype entity mention embedding
Yixin Cao, Lifu Huang, Heng Ji, Xu Chen, and Juanzi Li. 2017 · 2017
Cited alongside, same era.
Named entity disambiguation for noisy text
Yotam Eshel, Noam Cohen, Kira Radinsky, Shaul Markovitch, Ikuya Yamada, and Omer Levy. 2017 · 2017
Cited alongside, same era.
Deep joint entity disambiguation with local neural attention
Joint representation learning of cross-lingual words and entities via attentive distant supervision
Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu, Chengjiang Li, Xu Chen, and Tiansi Dong. 2018 · 2018
Later among the works it cites.
Systematic study of long tail phenomena in entity linking
Filip Ilievski, Piek Vossen, and Stefan Schlobach. 2018 · 2018
Later among the works it cites.
End-to-end neural entity linking
Nikolaos Kolitsas, Octavian-Eugen Ganea, and Thomas Hofmann. 2018 · 2018
Later among the works it cites.
Improving entity linking by modeling latent relations between mentions
Phong Le and Ivan Titov. 2018 · 2018
Later among the works it cites.
GERBIL - benchmarking named entity recognition and linking consistently
Michael Röder, Ricardo Usbeck, and Axel-Cyrille Ngonga Ngomo. 2018 · 2018
Later among the works it cites.
Neural cross-lingual entity linking
Avirup Sil, Gourab Kundu, Radu Florian, and Wael Hamza. 2018 · 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Octavian-Eugen Ganea and Thomas Hofmann. 2017 · 2017
Cited alongside, same era.
Google’s multilingual neural machine translation system: Enabling zero-shot translation
Melvin Johnson, Mike Schuster, Quoc V. Le, Maxim Krikun, Yonghui Wu, Zhifeng Chen, Nikhil Thorat, Fernanda Viégas, Martin Wattenberg, Greg Corrado, Macduff Hughes, and Jeffrey Dean. 2017 · 2017
Cited alongside, same era.
Yolo9000: Better, faster, stronger
J. Redmon and A. Farhadi. 2017 · 2017
Cited alongside, same era.
Learning distributed representations of texts and entities from knowledge base
Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda, and Yoshiyasu Takefuji. 2017 · 2017
Cited alongside, same era.
Learning text representations for 500K classification tasks on named entity disambiguation
Ander Barrena, Aitor Soroa, and Eneko Agirre. 2018 · 2018
Cited alongside, same era.
Later among the works it cites.
Wikipedia2vec: An optimized tool for learning embeddings of words and entities from wikipedia
Ikuya Yamada, Akari Asai, Hiroyuki Shindo, Hideaki Takeda, and Yoshiyasu Takefuji. 2018 · 2018
Later among the works it cites.
Investigating entity knowledge in BERT with simple neural end-to-end entity linking
Samuel Broscheit. 2019 · 2019
Closest in time.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Closest in time.
Joint learning of named entity recognition and entity linking
Pedro Henrique Martins, Zita Marinho, and André F. T. Martins. 2019 · 2019
Closest in time.