A significant portion of experimental data in materials science remains locked within the confines of literature . Unlocking this wealth of high-quality data presents an opportunity to revolutionize materials informatics, potentially leading to the creation of databases that could, overnight, transform the field. Indeed, such databases have already However, existing databases in the field often revolve around calculated materials properties , introducing potential systematic errors and limiting the scope of data to quantities amenable to rapid computations. Additionally, there exists the risk that such calculations may not accurately reflect real-world scenarios. This suboptimal reliance on calculated properties highlights the need for more comprehensive and accessible experimental databases. While some attempts at constructing experimental databases exist, they often remain proprietary due to the associated labor costs . Although a few open-access initiatives have initiated database construction efforts , there is still ample room for the development of workflows aimed at enhancing accessibility and performance in automated materials database construction from literature-a fertile area for investigation. Our JSON structured data extraction method emerges as a promising avenue in this exploration.