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This paper describes our participation in the SemEval-2020 task Detection ofPropaganda Techniques in News Articles. We participate in both subtasks: SpanIdentification (SI) and Technique Classification (TC). We use a bi-LSTMarchitecture in the SI subtask and train a complex ensemble model for the TCsubtask. Our architectures are built using embeddings from BERT in combinationwith additional lexical features and extensive label post-processing. Oursystems achieve a rank of 8 out of 35 teams in the SI subtask (F1-score:43.86%) and 8 out of 31 teams in the TC subtask (F1-score: 57.37%).

CyberWallE at SemEval-2020 Task 11: An Analysis of Feature Engineering for Ensemble Models for Propaganda Detection