To provide insights into the model's performance without human intervention, we generated five additional examples solely using Gemini Pro. We then compared these examples with the gold standard examples prepared by our semi-automated approach, which involved human annotators collaborating with Gemini Pro. The average scores of these five examples were calculated for each metric, considering the stochasticity inherent in language models. These results will help us to assess the model's performance and provided valuable insights into the level of human intervention required to achieve high-quality annotations.