Understanding causality is a core aspect of intelligence. The Event Causality Identification with Causal News Corpus Shared Task addresses two aspects of this challenge: Subtask 1 aims at detecting causal relationships in texts, and Subtask 2 requires identifying signal words and the spans that refer to the cause or effect, respectively. Our system, which is based on pre-trained transformers, stacked sequence tagging, and synthetic data augmentation, ranks third in Subtask 1 and wins Subtask 2 with an F1 score of 72.8, corresponding to a margin of 13 pp. to the second-best system.

翻译：理解因果性是智能的核心维度。因果新闻语料库中的事件因果识别共享任务针对该挑战的两个方面展开：子任务1旨在检测文本中的因果关系，子任务2要求分别识别信号词以及指代原因或结果的文本跨度。我们的系统基于预训练Transformer、堆叠序列标注与合成数据增强技术，在子任务1中位列第三，并以72.8的F1分数（高出第二名系统13个百分点）赢得子任务2。