```json { "table_name": "report_insights", "table_type_tags": [ {"tag": "event", "confidence": 0.75}, {"tag": "dimension", "confidence": 0.30} ], "primary_type": "event", "insufficient_evidence": false, "entity": { "columns": ["jobs_id"], "unique_per_row": false }, "time_axis": { "columns": ["index"], "kind": "sequence" }, "reasoning": "The entity jobs_id repeats (RPUV 11.91, Uniqueness 0.084) along the sequence axis index (Monotonicity 0.917, values 0–67). Each row records a discrete insight message generated during a job run — table_count, column_range, or other findings — ordered by index within the job. The rows are bare occurrences to count and analyze (insight types, message patterns), not state transitions that replay into a meaningful entity state. The kind column (Top 3 Coverage 100%, only 3 values) categorizes the insight type. Secondary dimension reading: if each (jobs_id, index) combination were unique, the rows would be a catalog of insights, but RPUV on index (20.31) shows the sequence repeats across jobs, confirming the event structure." } ```