Repackaging Temporal Evidence: A Unifying Interface for Temporal Prediction

Temporal tabular prediction and irregular time-series prediction often arise from similar longitudinal records, but they expose different evidence at query time. Temporal tables usually present a timestamped covariate row and evaluate generalization to future periods, whereas irregular time-series protocols present entity-specific observations and query values at selected times. We study this gap as a protocol issue rather than a modality boundary. We introduce a unified prediction interface that specifies the query-time information set and the prediction rule applied to it, and use it to diagnose protocol mismatches in cross-domain reuse. The interface highlights two common failures: entity collapse, where a temporal table is forced into a single sequence across unrelated entities, and temporal relation mismatch, where tabulation hides the within-sequence structure expected by a time-series model. Empirically, we use the interface as a diagnostic tool in both directions. A retrieval-based tabular predictor can be evaluated on irregular time-series tasks once candidate sets are repackaged as temporally embedded, entity-specific contexts. Conversely, selected temporal tables admit time-series evaluations when recoverable entity histories or source sequences are restored before modeling. These results highlight repackaging temporal evidence as a way to enable cross-domain reuse, without implying that either model family subsumes the other.