By examining examples in which a model trained on OC and VG made correct predictions as opposed to a model trained on PE, we quickly noticed that lexical indicators indeed played a crucial role.
the occurrence of the word "should" (and to a lower degree: "would", "article", "one") are helpful for the detection of claims across various datasets.