NoPropaganda at SemEval-2020 Task 11: A Borrowed Approach to Sequence Tagging and Text Classification

التفاصيل البيبلوغرافية
العنوان: NoPropaganda at SemEval-2020 Task 11: A Borrowed Approach to Sequence Tagging and Text Classification
المؤلفون: Dimov, Ilya, Korzun, Vladislav, Smurov, Ivan
سنة النشر: 2020
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computation and Language
الوصف: This paper describes our contribution to SemEval-2020 Task 11: Detection Of Propaganda Techniques In News Articles. We start with simple LSTM baselines and move to an autoregressive transformer decoder to predict long continuous propaganda spans for the first subtask. We also adopt an approach from relation extraction by enveloping spans mentioned above with special tokens for the second subtask of propaganda technique classification. Our models report an F-score of 44.6% and a micro-averaged F-score of 58.2% for those tasks accordingly.
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2007.12913
رقم الأكسشن: edsarx.2007.12913
قاعدة البيانات: arXiv