RESEARCH · RESEARCH · #646
Glyph: multi-strategy agentic system for column description and sensitivity-ontology tagging
Glyph is a production system framing column-description generation and column-type annotation as cooperating stateful LLM agents. The Descriptor grounds descriptions in pipeline source code retrieved from enterprise GitHub via an active RAG loop, while the Tagger runs three parallel strategies (description-based, regex-based, and a fine-tuned MiniLM contrastive metadata encoder over a vector DB) and fuses ranked outputs with Reciprocal Rank Fusion; the paper reports large retrieval gains (NDCG@10 0.55→0.92, MAP@100 0.19→0.90) and evaluates end-to-end multi-label tagging with ablations and provenance-enabled, value-free, code-grounded design choices.
KEY POINTS
- Glyph is a production system framing column-description generation and column-type annotation as cooperating stateful LLM agents.
- The Descriptor grounds descriptions in pipeline source code retrieved from enterprise GitHub via an active RAG loop, while the Tagger runs three parallel strategies (description-based, regex-based, and a fine-tuned MiniLM contrastive metadata encoder over a vector DB) and fuses ranked outputs with Reciprocal Rank Fusion; the paper reports large retrieval gains (NDCG@10 0.55→0.92, MAP@100 0.19→0.90) and evaluates end-to-end multi-label tagging with ablations and provenance-enabled, value-free, code-grounded design choices.
- Automating code-grounded, multi-strategy tagging with per-tag provenance addresses documentation debt in enterprise data catalogs, improving discoverability, governance, and auditable compliance.
WHY IT MATTERS
Automating code-grounded, multi-strategy tagging with per-tag provenance addresses documentation debt in enterprise data catalogs, improving discoverability, governance, and auditable compliance.