What is Semantic Join
Semantic Join - A cross-collection enrichment operation that attaches context from one collection to results from another, using semantic similarity as the join key.
A semantic join is the multimodal equivalent of a SQL JOIN. In structured databases, JOINs combine rows from different tables using foreign keys. In a multimodal data warehouse, enrich stages combine results from different collections using embedding similarity or document relationships. This enables cross-referencing without pre-defined foreign keys.
How It Works
After a retrieval pipeline produces results from one collection (e.g., media library search), an enrich stage queries a second collection (e.g., brand safety scores) to attach contextual data to each result. The join can be by document ID, semantic similarity, or metadata matching.
Examples
- Search media library for celebrity appearances → enrich with brand safety scores from a separate collection
- Find similar products → enrich with pricing and availability from a catalog collection
- Detect copyrighted audio → enrich with licensing terms from a rights database
- Find relevant document passages → enrich with author and classification metadata
Best Practices
- Use enrich stages after reduce stages to minimize the number of cross-collection lookups
- Keep enrichment collections focused: one collection per enrichment type (brand scores, rights, metadata)
- Use semantic joins for fuzzy matching and document_enrich for exact ID-based joins
Related Pages
- Document Enrich stage: /docs/retrieval/stages/document-enrich
- Retrieval Cookbook: /docs/retrieval/cookbook
- Blog: Multi-Stage Retrieval Pipelines - /blog/multi-stage-retrieval-pipelines