where T P (true positives) and T N (true negatives) indicate labels predicted by chatGPT that matched our analysis, and FP (false positives) represent labels assigned as positive by the model, but as negative in our manual analysis. For the particular where we observed chatGPT did not perform as accurately, we resorted to a manual analysis to remove erroneous relations obtained. Guaranteed the effectiveness of our approach and the quality of our dataset, we utilized sentences recognized as relevant in the downstream task of linking elements, products, and FEs from the papers in our corpus.