Overview of the EVALITA 2016 Named Entity rEcognition and Linking in Italian Tweets (NEEL-IT) Task

English. This report describes the main outcomes of the 2016 Named Entity rEcognition and Linking in Italian Tweet (NEEL-IT) Challenge. The goal of the challenge is to provide a benchmark corpus for the evaluation of entity recognition and linking algorithms specifically designed for noisy and short texts, like tweets, written in Italian. The task requires the correct identification of entity mentions in a text and their linking to the proper named entities in a knowledge base. To this aim, we choose to use the canonicalized dataset of DBpedia 201510. The task has attracted five participants, for a total of 15 runs submitted. Italiano. In questo report descriviamo i principali risultati conseguiti nel primo task per la lingua Italiana di Named Entity rEcognition e Linking in Tweet (NEELIT). Il task si prefigge l’obiettivo di offrire un framework di valutazione per gli algoritmi di riconoscimento e linking di entità a nome proprio specificamente disegnati per la lingua italiana per testi corti e rumorosi, quali i tweet. Il task si compone di una fase di riconoscimento delle menzioni di entità con nome proprio nel testo e del loro successivo collegamento alle opportune entità in una base di conoscenza. In questo task abbiamo scelto come base di conoscenza la versione canonica di DBpedia 2015. Il task ha attirato cinque partecipanti per un totale di 15 diversi run.

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