March 2025 monthly summary for OpenSPG/KAG. Delivered a new Table Extraction Pipeline and Markdown Table Support to enable structured knowledge graph generation from tabular data. Implemented TableExtractor component and integrated with NaiveRagExtractor to process table chunks; updated MarkdownReader to accurately identify and process table elements. This work reduced manual data wrangling, improved extraction quality, and enhanced searchability for tabular sources. No major bugs reported in this period; focus remained on feature delivery and stability. Business impact includes improved data ingestion from tables, richer knowledge graphs, faster time-to-insight for tabular sources, and a stronger foundation for table-driven analytics. Technologies/skills demonstrated include ETL/knowledge graph pipelines, Python component design, integration with Rag-based retrieval, and Markdown parsing enhancements.

February 2025 monthly summary for OpenSPG/openspg focused on correctness and reliability of the Reasoner, with targeted bug fix, regression testing, and code improvements to edge handling. Delivered a high-impact fix that reduces erroneous repeat matches in graphs containing optional and repeating edges, complemented by regression coverage and code refinements to ensure future stability.