Beyond lexical and embedding-based retrieval, metadata-driven retrieval offers a third approach where queries are decomposed into structured attributes (color, material, category) and ranked accordingly. This enables explainable, testable ranking that stakeholders can reason about in plain language. With LLMs making query and content classification trivially easy, many search problems previously requiring deep NLP research can now be solved through simple attribute matching and stakeholder conversations, without complex user evaluations.
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