benzsevern/goldenmatch — Polyglot data-quality + entity-resolution toolkit with introspective auto-config: zero-config beats…

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.

Problem

benzsevern/goldenmatch helps connect AI assistants to real tools and data through a standard protocol.

Outcome

Medium: useful for prototypes or internal workflows, with dependency and maintenance checks before production.

Workflow

• connect AI agents to tools
• ship Model Context Protocol servers
• standardize integrations

Evidence

Polyglot data-quality + entity-resolution toolkit with introspective auto-config: zero-config beats hand-tuned on DBLP-ACM (0.96 F1), Febrl3 (0.94 F1), NCVR (0.97 F1). GoldenCheck profiles -> GoldenFlow standardizes -> GoldenMatch dedupes -> GoldenPipe orchestrates. MCP per package, multi-arch containers, Airflow DAGs, browser workbench.

Source