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Bridge the Last-Mile Gap to Semantic Analytics: Compiling Natural-Language Queries into Semantic Operator Pipelines
arXiv:2606.04641v1 Announce Type: new Abstract: Automated AI workflows increasingly rely on natural-language reasoning over heterogeneous data, but lack a practical way to execute it through optimized semantic data systems. Recent semantic operator systems, such as Palimpzest and LOTUS, expose declarative operators for filtering, joining, mapping, and aggregating over tables, text, and images using natural-language predicates. However, these systems require users to manually choose...