Word Embeddings for Unsupervised Named Entity Linking

Author:

Nozza DeboraORCID,Sas CezarORCID,Fersini ElisabettaORCID,Messina EnzaORCID

Publisher

Springer International Publishing

Reference44 articles.

1. Basile, P., Caputo, A., Gentile, A.L., Rizzo, G.: Overview of the EVALITA 2016 Named Entity rEcognition and Linking in Italian Tweets (NEEL-IT) Task. In: Proceedings of 3rd Italian Conference on Computational Linguistics & 5th Evaluation Campaign of Natural Language Processing and Speech Tools for Italian, vol. 1749 (2016)

2. Basile, P., Caputo, A., Semeraro, G., Narducci, F.: UNIBA: exploiting a distributional semantic model for disambiguating and linking entities in tweets. In: Proceedings of the 5th Workshop on Making Sense of Microposts Co-located with the 24th International World Wide Web Conference, vol. 1395, p. 62 (2015)

3. Basile, P., et al. (eds.): Proceedings of 3rd Italian Conference on Computational Linguistics & 5th Evaluation Campaign of Natural Language Processing and Speech Tools for Italian, vol. 1749 (2016)

4. Bunescu, R.C., Pasca, M.: Using encyclopedic knowledge for named entity disambiguation. In: Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics (2006)

5. Caliano, D., Fersini, E., Manchanda, P., Palmonari, M., Messina, E.: UniMiB: entity linking in tweets using Jaro-Winkler distance, popularity and coherence. In: Proceedings of the 6th Workshop on Making Sense of Microposts Co-located with the 25th International World Wide Web Conference, vol. 1691, pp. 70–72 (2016)

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