What Features Enable Reliable Document Version Selection in RAG?
Reliable version selection requires treating document identity and temporal validity as retrieval constraints, not hoping vector similarity will prefer the newest text.
A NAS may retain several appliance manuals, insurance policies, or edited family plans whose wording is nearly identical. Dense search can rank an obsolete revision above the current one because relevance and validity are different signals. A version-aware pipeline stores immutable revisions, models supersession and effective dates, interprets the query’s time, and cites the exact revision used.
Stable Source and Revision IDs Separate Identity From Location
One logical document keeps a stable source ID while every captured revision receives an immutable revision ID, content hash, ingestion time, effective interval, lifecycle state, and path mapping. Chunks inherit both identifiers instead of carrying a vague “latest” label.
The version-aware retrieval framework explicitly models version sequences, content boundaries, and changes, reporting large gains over naive RAG on version-sensitive questions. Its design shows why similar text requires structural version information. This distinction remains visible during later household testing.
Supersession links express whether a revision fully replaces an earlier document, amends only sections, or remains valid for a different product version. Path modification time alone cannot represent those relationships and may reflect copying rather than effective validity.
Query Time and Applicability Must Enter Retrieval
A query may ask for the current rule, a rule as of last year, or instructions for a specific firmware version. The query processor extracts explicit and implicit temporal constraints plus product, jurisdiction, owner, and lifecycle context before candidate ranking.
A temporal retrieval constraints dataset study explains how semantic matching can retrieve outdated evidence when questions contain temporal constraints. It supports evaluating time-sensitive retrieval separately from static factual recall. The intermediate result must remain inspectable before automation follows.
Filtering can select eligible revisions before vector search, while temporal scoring can rerank overlapping candidates afterward. The system should not always favor the newest file: historical questions require the revision valid at the requested time.
Overlapping Amendments Need Conflict and Lineage Logic
Some updates replace one clause while leaving the rest of the document effective. Splitting each snapshot into independent chunks creates many near-duplicates and can combine an old amended clause with current unchanged material. Version lineage needs section-level boundaries and validity.
The semantic-temporal retrieval approach combines semantic and temporal relevance for overlapping evolving documents and reports gains in nDCG@10. This demonstrates why time is not merely a metadata tie-breaker when amendments remain semantically similar. That boundary should be measured separately under realistic operating conditions.
The failure boundary is unknown applicability. Missing effective dates, ambiguous filenames, or conflicting active revisions should trigger clarification or abstention, not an automatic “latest” choice. Preserve the competing candidates and their metadata so a reviewer can resolve the source record.
Test Current, Historical, and Ambiguous Version Queries
Build a fixture with full replacements, partial amendments, backdated revisions, duplicate copies, renamed files, drafts, archived versions, and one document missing an effective date. Label the correct revision or expected abstention for each question. The practical consequence appears when several sources compete for limited context.
Compare selection with the lineage chain in answer source lineage. Measure eligible-version recall, wrong-version rate, mixed-version answers, citation resolution, and handling of explicit dates, relative dates, firmware versions, and current-state questions. This dependency should remain explicit in the final interface.
Pass only when every answer cites the applicable immutable revision and ambiguous cases remain unresolved. If adding recency boosts current queries but breaks historical ones, separate applicability filtering from general ranking instead of increasing one freshness weight.
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