Synthetic Causal Relations

该数据集是为了实验假新闻检测而生成的，包含有因果关系的合成数据。数据集中涉及的形式为A导致B和B导致C的因果关系，这些关系是利用特定的副词和概率分布生成的。规模上，每个合成实验的训练集包含200个因果关系，测试集包含5个。该数据集的任务是基于因果关系的假新闻检测与分类。

This dataset is developed for fake news detection experiments and consists of synthetic data with causal relationships. These causal relationships take the form of 'A causes B' and 'B causes C', and are generated using specific adverbs and probability distributions. In terms of scale, the training set for each synthetic experiment contains 200 causal relationships, while the test set includes 5 instances. The core task of this dataset is fake news detection and classification grounded in causal relationships.