YNUtaoxin at SemEval-2020 Task 11: Identification Fragments of Propaganda Technique by Neural Sequence Labeling Models with Different Tagging Schemes and Pre-trained Language Model

Abstract

Information extraction is a hot topic in NLP, and detecting the use of propaganda techniques in news articles is part of this kind of task. This paper describes the solution of the Span Identification subtask in the Semeval 2020 Task 11: Detection of Propaganda Techniques in News Articles. The core idea of our method is equivalent to regard this task as a sequence tagging task and develop a neural sequence model to solve it. We use three different tagging schemes to tag sentences. Some pre-trained language models are used as the feature encoder like BERT, RoBERTa, and XLNet. In the final evaluation, we achieve the F1-score of 0.43208 and rank 11th among all the submitted teams.