Worked on enhancing XBRL processing capabilities within the DS4SD/docling repository by implementing robust fact and context extraction features. Leveraged Python to develop backend data parsing routines that accurately identify and map relationships using XBRL linkbases, enabling more comprehensive discovery of data relationships within financial documents. The technical approach focused on scalable parsing logic and clear documentation, supporting downstream analytics and regulatory reporting needs. This work improved both data quality and processing efficiency for XBRL documents, laying a foundation for more reliable and maintainable backend systems. The contribution emphasized XBRL standards, backend development, and advanced data parsing techniques throughout the project.