  This paper describes our submission for the subjectivity detection task at
the CheckThat! Lab. To tackle class imbalances in the task, we have generated
additional training materials with GPT-3 models using prompts of different
styles from a subjectivity checklist based on journalistic perspective. We used
the extended training set to fine-tune language-specific transformer models.
Our experiments in English, German and Turkish demonstrate that different
subjective styles are effective across all languages. In addition, we observe
that the style-based oversampling is better than paraphrasing in Turkish and
English. Lastly, the GPT-3 models sometimes produce lacklustre results when
generating style-based texts in non-English languages.
