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28 août 2017
- doi: 10.4000/books.aaccademia.1938
- eisbn: 9788899982553
https://creativecommons.org/licenses/by-nc-nd/4.0/ , info:eu-repo/semantics/openAccess
Mots-clés
linguistica computazionale riconoscimento telefonico articolare annotazione fattualità degli eventi entità chiamata rEcognition e collegamenti nei tweet italiani etichettare per messaggi social media classificazione polarità sentimenti linguistique computationelle reconnaissance téléphonique articulatoire annotation de facturation de l'événement entité appelée rEcognition et liens dans le tweets italien étiqueter les messages des médias sociaux classement polarité sentiments computational linguistics articulatory phone recognition event factuality annotation named entity rEcognition and linking in italian tweets tagging for italian social media texts sentiment polarity classification LAN009000 Linguistics CFSujets proches
Fields, Random User-generated mediaCiter ce document
Flavio Massimiliano Cecchini et al., « UNIMIB@NEEL-IT : Named Entity Recognition and Linking of Italian Tweets », Accademia University Press, ID : 10.4000/books.aaccademia.1938
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Résumé
This paper describes the framework proposed by the UNIMIB Team for the task of Named Entity Recognition and Linking of Italian tweets (NEEL-IT). The proposed pipeline, which represents an entry level system, is composed of three main steps: (1) Named Entity Recognition using Conditional Random Fields, (2) Named Entity Linking by considering both Supervised and Neural-Network Language models, and (3) NIL clustering by using a graph-based approach.