```json { "table_name": "deleted_datasets", "primary_key": "dataset_id", "candidates": [ { "rank": 0, "partition_key": "dataset_id", "partition_key_label": "E", "partition_key_reasoning": "Entity column identified by classifier. RPUV=1.00 (9 unique values for 9 rows), uniqueness=1.000. Each dataset_id represents a distinct dataset entity whose deletion lifecycle is being tracked. Semantic role: the primary entity whose path through creation→deletion→purge is recorded.", "clustering_key": "deleted_at", "clustering_key_label": "S", "clustering_key_reasoning": "Primary temporal ordering axis for the deletion lifecycle. RPUV=1.00, uniqueness=1.000. Represents the key event timestamp in the deletion path. Orders the lifecycle events chronologically (created_at < deleted_at < purged_at).", "world_line": "dataset_id", "session_column": null, "confidence": "HIGH", "notes": "This is a path table tracking the deletion lifecycle of datasets. Each row represents one dataset's journey through creation, deletion, and purging. The dataset_id is the entity (E) being tracked, and deleted_at is the primary sequence marker (S). With only 9 rows and perfect uniqueness on dataset_id, this is effectively a dimension-like snapshot of deleted datasets, but the presence of multiple temporal markers (created_at, deleted_at, purged_at) and the path classification indicate it captures lifecycle events." } ] } ```