benzsevern/goldenmatch
Description and use
GoldenMatch is a polyglot data‑quality and entity‑resolution toolkit that automatically configures itself to achieve state‑of‑the‑art deduplication results (e.g., 0.96 F1 on DBLP‑ACM, 0.94 F1 on Febrl3, 0.97 F1 on NCVR) without manual tuning. The workflow starts with GoldenCheck profiling, passes through GoldenFlow standardization, runs GoldenMatch for deduplication, and is orchestrated by GoldenPipe, with each component packaged as multi‑arch containers, exposed via Airflow DAGs and a web‑based workbench. It targets AI/ML, backend, and data engineering use cases.
Use in a workflow
benzsevern/goldenmatch helps connect AI assistants to real tools and data through a standard protocol.
- connect AI agents to tools
- ship Model Context Protocol servers
- standardize integrations
Limitations and review notes
Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.
- Source: github
- Language: Python
- Record date: 2026-09-05T17:30:50.240Z