A Report on the DSL Shared Task 2014
Marcos Zampieri, Liling Tan, Nikola Ljubešić, Jörg Tiedemann · 2014
This paper summarizes the methods, results and findings of the Discriminating between Similar Languages (DSL) shared task 2014.The shared task provided data from 13 different languages and varieties divided into 6 groups.Participants were required to train their systems to discriminate between languages on a training and development set containing 20,000 sentences from each language (closed submission) and/or any other dataset (open submission).One month later, a test set containing 1,000 unidentified instances per language was released for evaluation.The DSL shared task received 22 inscriptions and 8 final submissions.The best system obtained 95.7% average accuracy.