A. Alhelbawy and R. Gaizauskas, Graph ranking for collective named entity disambiguation, Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, vol.2, pp.75-80, 2014.

R. Blanco, G. Ottaviano, and E. Meij, Fast and space-efficient entity linking for queries, Proceedings of the 8th ACM International Conference on Web Search and Data Mining, pp.179-188, 2015.

P. Bojanowski, E. Grave, A. Joulin, and T. Mikolov, Enriching word vectors with subword information, Transactions of the Association for Computational Linguistics, vol.5, pp.135-146, 2017.

K. Bollacker, C. Evans, P. Paritosh, T. Sturge, and J. Taylor, Freebase: a collaboratively created graph database for structuring human knowledge, Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp.1247-1250, 2008.

R. Bunescu and M. Pa?ca, Using encyclopedic knowledge for named entity disambiguation, Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics, pp.9-16, 2006.

Y. Cao, L. Hou, J. Li, and Z. Liu, Neural collective entity linking, Proceedings of the 27th International Conference on Computational Linguistics, pp.675-686, 2018.

D. Ceccarelli, C. Lucchese, S. Orlando, R. Perego, and S. Trani, Learning relatedness measures for entity linking, Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, pp.139-148, 2013.

. Silviu-cucerzan, Large-scale named entity disambiguation based on Wikipedia data, Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pp.708-716, 2007.

M. Dredze, P. Mcnamee, D. Rao, A. Gerber, and T. Finin, Entity disambiguation for knowledge base population, Proceedings of the 23rd International Conference on Computational Linguistics, pp.277-285, 2010.

G. Durrett and D. Klein, A joint model for entity analysis: coreference, typing, and linking, Transactions of the Association for Computational Linguistics, vol.2, pp.477-490, 2014.

. John-r-firth, A synopsis of linguistic theory, Studies in linguistic analysis, pp.1930-1955, 1957.

M. Francis-landau, G. Durrett, and D. Klein, Capturing semantic similarity for entity linking with convolutional neural networks, Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp.1256-1261, 2016.

M. Octavian-eugen-ganea, A. Ganea, C. Lucchi, T. Eickhoff, and . Hofmann, Probabilistic bag-of-hyperlinks model for entity linking, Proceedings of the 25th International Conference on World Wide Web, pp.927-938, 2016.

E. Octavian, T. Ganea, and . Hofmann, Deep joint entity disambiguation with local neural attention, Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp.2619-2629, 2017.

N. Gupta, S. Singh, and D. Roth, Entity linking via joint encoding of types, descriptions, and context, Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pp.2681-2690, 2017.

J. Hoffart, M. A. Yosef, I. Bordino, H. Fürstenau, M. Pinkal et al., Robust disambiguation of named entities in text, Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pp.782-792, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01122678

H. Huang, L. Heck, and H. Ji, Leveraging deep neural networks and knowledge graphs for entity disambiguation, 2015.

H. Ji and . Nothman, Overview of TAC-KBP2016 tri-lingual EDL and its impact on end-to-end cold-start KBP, Proceedings of the 2016 Text Analysis Conference, 2016.

H. Ji, J. Nothman, B. Hachey, and R. Florian, Overview of TAC-KBP2015 tri-lingual entity discovery and linking, Proceedings of the 2015 Text Analysis Conference, 2015.

H. Ji, X. Pan, B. Zhang, J. Nothman, J. Mayfield et al., Overview of TAC-KBP2017 13 languages entity discovery and linking, Proceedings of the 2017 Text Analysis Conference, 2017.

N. Kolitsas, . Octavian-eugen, T. Ganea, and . Hofmann, End-toend neural entity linking, Proceedings of the 22nd Conference on Computational Natural Language Learning, pp.519-529, 2018.

P. Le and I. Titov, Improving entity linking by modeling latent relations between mentions, Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, pp.1595-1604, 2018.

X. Ling, S. Singh, and D. S. Weld, Design challenges for entity linking, Transactions of the Association for Computational Linguistics, vol.3, pp.315-328, 2015.

M. Liu, G. Gong, B. Qin, and T. Liu, A multi-view-based collective entity linking method, ACM Transactions on Information Systems, vol.37, 2019.

W. Lu, Y. Zhou, H. Lu, P. Ma, Z. Zhang et al., Boosting collective entity linking via type-guided semantic embedding, Proceedings of the National CCF Conference on Natural Language Processing and Chinese Computing, pp.541-553, 2017.

P. N. Mendes, M. Jakob, A. García-silva, and C. Bizer, DBpedia spotlight: shedding light on the web of documents, Proceedings of the 7th International Conference on Semantic Systems, pp.1-8, 2011.

T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean, Distributed representations of words and phrases and their compositionality, Proceedings of Advances in Neural Information Processing Systems, pp.3111-3119, 2013.

D. Milne and . Ian-h-witten, Learning to link with Wikipedia, Proceedings of the 17th ACM Conference on Information and Knowledge Management, pp.509-518, 2008.

J. G. Moreno, R. Besançon, R. Beaumont, A. Eva-d'hondt, S. Ligozat et al., Combining word and entity embeddings for entity linking, Proceedings of European Semantic Web Conference, pp.337-352, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01626196

A. Moro, A. Raganato, and R. Navigli, Entity linking meets word sense disambiguation: a unified approach, Transactions of the Association for Computational Linguistics, vol.2, pp.231-244, 2014.

J. Pennington, R. Socher, and C. Manning, Glove: global vectors for word representation, Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, pp.1532-1543, 2014.

M. C. Phan, A. Sun, Y. Tay, J. Han, and C. Li, Pairlinking for collective entity disambiguation: Two could be better than all, IEEE Transactions on Knowledge and Data Engineering, 2018.

M. Röder, R. Usbeck, S. Hellmann, D. Gerber, and A. Both, N 3 -A collection of datasets for named entity recognition and disambiguation in the NLP interchange format, Proceedings of the 9th International Conference on Language Resources and Evaluation, pp.3529-3533, 2014.

W. Shen, J. Wang, and J. Han, Entity linking with a knowledge base: Issues, techniques, and solutions, IEEE Transactions on Knowledge and Data Engineering, vol.27, pp.443-460, 2015.

I. Valentin, A. X. Spitkovsky, and . Chang, A cross-lingual dictionary for English Wikipedia concepts, Proceedings of the 8th International Conference on Language Resources and Evaluation, pp.3168-3175, 2012.

R. Usbeck, A. Ngomo, M. Röder, D. Gerber, S. A. Coelho et al., AGDISTIS -Graphbased disambiguation of named entities using linked data, Proceedings of the International Semantic Web Conference, pp.457-471, 2014.

R. Usbeck, M. Röder, A. Ngomo, C. Baron, A. Both et al., GERBIL: General entity annotator benchmarking framework, Proceedings of the 24th International Conference on World Wide Web, pp.1133-1143, 2015.

. W3c, RDF 1.1 Concepts and Abstract Syntax, 2014.

. W3c, , 2014.

. W3c, , 2014.

H. Wang, J. G. Zheng, X. Ma, P. Fox, and H. Ji, Language and domain independent entity linking with quantified collective validation, Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp.695-704, 2015.

I. Yamada, H. Shindo, H. Takeda, and Y. Takefuji, Joint learning of the embedding of words and entities for named entity disambiguation, Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning, pp.250-259, 2016.