FinReflectKG: Agentic Construction and Evaluation of Financial Knowledge Graphs
The financial domain poses unique challenges for knowledge graph (KG) construction at scale due to the complexity and regulatory nature of financial documents. Despite the critical importance of structured financial knowledge, the field lacks large-scale, open-source datasets capturing rich semantic relationships from corporate disclosures. We introduce an open-source, large-scale financial knowledge graph dataset built from the latest annual SEC 10-K filings of all S&P 100 companies - a comprehensive resource designed to catalyze research in financial AI.
Authors
- Stefano Pasquali (ORCID: https://orcid.org/0009-0007-8005-3207)
- Bhaskarjit Sarmah (ORCID: https://orcid.org/0009-0004-3076-9539)
- Fabrizio Dimino (ORCID: https://orcid.org/0009-0006-6723-1999)
- Abhinav Arun (ORCID: https://orcid.org/0009-0004-1188-1090)
- Tejas Prakash Agarwal (ORCID: https://orcid.org/0009-0004-2078-0419)
Institutions
- Becton Dickinson (India) (IN)
- Domus Medica (BE)
Publication Details
- Published
- 2025-11-14
- DOI
- https://doi.org/10.1145/3768292.3770363
- Citations
- 2
- Primary Topic
- Advanced Graph Neural Networks
- Type
- article
- Field-Weighted Citation Impact
- 4.96