Executable Schema Contracts: From Automatic Ingestion to Multi-Source Retrieval

• URL: http://arxiv.org/abs/2606.05415v1
• Date: Wed, 03 Jun 2026 20:28:36 GMT
• Title: Executable Schema Contracts: From Automatic Ingestion to Multi-Source Retrieval
• Abstract summary: Real-world data spans tables, documents, and semi-structured files with implicit semantics.<n>We present a system that automatically discovers an executable schema from raw multi-source data.
• Score: 19.3757623473603
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Real-world data spans tables, documents, and semi-structured files with implicit semantics. Querying this data requires integrating evidence across inconsistent schemas and formats, yet existing approaches either demand costly manual engineering or bypass structure entirely. We present a system that automatically discovers an executable schema from raw multi-source data and uses it as a shared contract for knowledge graph construction and query-time retrieval. A closed-world field catalog constrains LLM-based schema discovery to attested fields; deterministic structural analysis infers identity keys, foreign keys, and source hierarchy; and the resulting schema drives extraction, deduplication, and cross-source linking into a provenance-aware knowledge graph. At query time the schema -- optionally extended via a monotonic protocol -- conditions a multi-tool agent routing retrieval across structured lookup, graph traversal, and vector search, returning grounded answers with traceable citations. In controlled zero-shot comparisons using the same LLM, data, and evaluation harness, the system improves over retrieval-only and decomposition-based baselines across four QA benchmarks, with ablations showing that schema-conditioned routing, structural intelligence, and schema-guided construction each contribute to the gains.

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