The creation of examples within the structured prompt is a critical step. Users provide input-output pairs as examples to guide the model in generating outputs that align with the desired format. In our context, these examples showcase the expected structure of the structured JSON or abstractive summaries for materials science texts. Impor-Figure : Example Tasks: The image illustrates the application of our semi-automated annotation process to materials science literature. At the top, a sample input text is provided, showcasing the complexity of scientific content. Below, on the left, the structured JSON extraction task is demonstrated, where the input text is transformed into a structured JSON format using our approach. This process provides a solid foundation for human annotators to edit and correct any mistakes, ensuring accuracy and refinement. On the right, the abstractive summary extraction task is showcased, with the input text condensed into a concise summary. We've also included the prompt used for both the task. tantly, these examples serve as the basis for the model's subsequent output when presented with test examples.