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 2015-10. The task has attracted five participants, for a total of 15 runs submitted.