I need to identify the time dimension and analyze the trend. From the dataset card, I can see there are three temporal axes: - `Publication date` (1950-07-02..2026-07-31) - `Training time (hours)` (0.1..9022.8) - `Last modified` (2025-11-28 11:51:46..2026-08-07 16:42:25) The most relevant for analyzing overall trend is `Publication date`, which spans from 1950 to 2026 and likely represents when AI models were published/released. Let me query the trend of model publications over time: ```json { "action": "tool_call", "reasoning": "I need to analyze the trend of AI model publications over time. The Publication date column spans 1950-2026, making it the primary temporal dimension. I'll aggregate by year to see if the number of models is growing, shrinking, flat, or shows seasonal patterns.", "tool": "query_sql", "args": { "sql": "SELECT EXTRACT(YEAR FROM \"Publication date\") AS year, COUNT(*) AS model_count FROM raw.all_ai_models WHERE \"Publication date\" IS NOT NULL GROUP BY year ORDER BY year", "purpose": "Count AI models published per year to identify the overall temporal trend", "source": "raw" } } ```