28 août 2017
https://creativecommons.org/licenses/by-nc-nd/4.0/ , info:eu-repo/semantics/openAccess
Giuseppe Attardi et al., « Using Embeddings for Both Entity Recognition and Linking in Tweets », Accademia University Press, ID : 10.4000/books.aaccademia.1946
The paper describes our submissions to the task on Named Entity rEcognition and Linking in Italian Tweets (NEEL-IT) at Evalita 2016. Our approach relies on a technique of Named Entity tagging that exploits both character-level and word-level embeddings. Character-based embeddings allow learning the idiosyncrasies of the language used in tweets. Using a full-blown Named Entity tagger allows recognizing a wider range of entities than those well known by their presence in a Knowledge Base or gazetteer. Our submissions achieved first, second and fourth top official scores.