ProTestA: Identifying and Extracting Protest Events in News Notebook for ProtestNews Lab at CLEF 2019

This notebook describes our participation to the Protest- New Lab, identifying protest events in news articles in English. Systems are challenged to perform unsupervised domain adaptation against three sub-tasks: document classification, sentence classification, and event ex- traction. We describe the final submitted systems for all sub-tasks, as well as a series of negative results. Results indicate pretty robust perfor- mances in all tasks (average F1 of 0.705 for the document classification sub-task, average F1 of 0.592 for the sentence classification sub-task; av- erage F1 0.528 for the event extraction sub-task), ranking in the top 4 systems, although drops in the out-of-domain test sets are not minimal