论文标题
Semeval-2020任务11：在新闻文章中检测宣传技术
SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles
论文作者
论文摘要
我们介绍了Semeval-2020任务11在新闻文章中检测宣传技术的结果和主要发现。该任务具有两个子任务。子任务SI是关于跨度识别的：给定平坦文本文档，发现包含宣传的特定文本片段。子任务TC是关于技术分类的：在完整文档的背景下，给定特定的文本片段，确定其使用的宣传技术，从14个可能的宣传技术的清单中选择。这项任务吸引了大量参与者：250支球队签约参加参加，44个在测试集上提交了一份。在本文中，我们介绍任务，分析结果，并讨论系统提交的内容及其使用的方法。对于两个子任务，最好的系统都使用了预训练的变压器和合奏。
We present the results and the main findings of SemEval-2020 Task 11 on Detection of Propaganda Techniques in News Articles. The task featured two subtasks. Subtask SI is about Span Identification: given a plain-text document, spot the specific text fragments containing propaganda. Subtask TC is about Technique Classification: given a specific text fragment, in the context of a full document, determine the propaganda technique it uses, choosing from an inventory of 14 possible propaganda techniques. The task attracted a large number of participants: 250 teams signed up to participate and 44 made a submission on the test set. In this paper, we present the task, analyze the results, and discuss the system submissions and the methods they used. For both subtasks, the best systems used pre-trained Transformers and ensembles.
