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  1. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_0a968753a30776d8/cli/conversation.jsonl +2 -0
  2. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_0a968753a30776d8/cli/session_summary.json +25 -0
  3. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_0a968753a30776d8/cli/sql_attempt_1.metadata.json +45 -0
  4. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_0a968753a30776d8/cli/sql_prompt_attempt_1.txt +180 -0
  5. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_0a968753a30776d8/cli/sql_response_attempt_1.raw.txt +4 -0
  6. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_0a968753a30776d8/cli/sql_response_attempt_1.txt +1 -0
  7. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_0a968753a30776d8/cli/sql_stderr_attempt_1.txt +0 -0
  8. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_attempt_1.metadata.json +43 -0
  9. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_attempt_2.metadata.json +43 -0
  10. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_prompt_attempt_1.txt +178 -0
  11. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_prompt_attempt_2.txt +178 -0
  12. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_response_attempt_1.raw.txt +4 -0
  13. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_response_attempt_1.txt +4 -0
  14. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_response_attempt_2.raw.txt +4 -0
  15. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_response_attempt_2.txt +4 -0
  16. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_stderr_attempt_1.txt +0 -0
  17. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_stderr_attempt_2.txt +0 -0
  18. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1ef2d9144d994e4b/cli/sql_attempt_1.metadata.json +43 -0
  19. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1ef2d9144d994e4b/cli/sql_attempt_2.metadata.json +43 -0
  20. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1ef2d9144d994e4b/cli/sql_prompt_attempt_1.txt +180 -0
  21. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1ef2d9144d994e4b/cli/sql_prompt_attempt_2.txt +180 -0
  22. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1ef2d9144d994e4b/cli/sql_response_attempt_1.raw.txt +4 -0
  23. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1ef2d9144d994e4b/cli/sql_response_attempt_1.txt +4 -0
  24. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1ef2d9144d994e4b/cli/sql_response_attempt_2.raw.txt +4 -0
  25. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1ef2d9144d994e4b/cli/sql_response_attempt_2.txt +4 -0
  26. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1ef2d9144d994e4b/cli/sql_stderr_attempt_1.txt +0 -0
  27. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1ef2d9144d994e4b/cli/sql_stderr_attempt_2.txt +0 -0
  28. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_25608dad21edeaa5/cli/sql_attempt_1.metadata.json +43 -0
  29. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_25608dad21edeaa5/cli/sql_attempt_2.metadata.json +43 -0
  30. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_25608dad21edeaa5/cli/sql_prompt_attempt_1.txt +183 -0
  31. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_25608dad21edeaa5/cli/sql_prompt_attempt_2.txt +183 -0
  32. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_25608dad21edeaa5/cli/sql_response_attempt_1.txt +4 -0
  33. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_25608dad21edeaa5/cli/sql_response_attempt_2.raw.txt +4 -0
  34. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_25608dad21edeaa5/cli/sql_response_attempt_2.txt +4 -0
  35. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_25608dad21edeaa5/cli/sql_stderr_attempt_1.txt +0 -0
  36. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_25608dad21edeaa5/cli/sql_stderr_attempt_2.txt +0 -0
  37. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_3c72e3519211cdf0/cli/sql_attempt_1.metadata.json +43 -0
  38. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_3c72e3519211cdf0/cli/sql_attempt_2.metadata.json +43 -0
  39. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_3c72e3519211cdf0/cli/sql_prompt_attempt_1.txt +180 -0
  40. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_3c72e3519211cdf0/cli/sql_prompt_attempt_2.txt +180 -0
  41. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_3c72e3519211cdf0/cli/sql_response_attempt_1.raw.txt +4 -0
  42. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_3c72e3519211cdf0/cli/sql_response_attempt_1.txt +4 -0
  43. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_3c72e3519211cdf0/cli/sql_response_attempt_2.raw.txt +4 -0
  44. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_3c72e3519211cdf0/cli/sql_response_attempt_2.txt +4 -0
  45. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_3c72e3519211cdf0/cli/sql_stderr_attempt_1.txt +0 -0
  46. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_3c72e3519211cdf0/cli/sql_stderr_attempt_2.txt +0 -0
  47. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_4093d2e88507df7c/cli/sql_attempt_2.metadata.json +43 -0
  48. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_50ce62738fb74973/cli/sql_attempt_1.metadata.json +43 -0
  49. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_50ce62738fb74973/cli/sql_attempt_2.metadata.json +43 -0
  50. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_50ce62738fb74973/cli/sql_prompt_attempt_1.txt +180 -0
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_0a968753a30776d8/cli/conversation.jsonl ADDED
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+ {"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 5947, "bytes_utf8": 5947, "lines": 180, "estimated_tokens": null}}
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+ {"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 426, "bytes_utf8": 426, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 13807, "cached_input_tokens": 12032, "output_tokens": 424, "reasoning_output_tokens": 309}}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_0a968753a30776d8/cli/session_summary.json ADDED
@@ -0,0 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "engine": "v2-cli:codex",
3
+ "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
4
+ "ai_cli_calls": 1,
5
+ "usage_summary": {
6
+ "dataset_id": "c20",
7
+ "model": "v2-cli:codex",
8
+ "run_id": "v2q_c20_0a968753a30776d8",
9
+ "api_calls": 0,
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+ "input_tokens": 13807,
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+ "cached_input_tokens": 12032,
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+ "output_tokens": 424,
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+ "total_tokens": 14231,
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+ "cost_usd": 0.0,
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+ "ai_cli_calls": 1,
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+ "estimated_input_tokens": 0,
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+ "estimated_output_tokens": 0,
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+ "estimated_total_tokens": 0,
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+ "usage_source": "ai_cli_json_usage",
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+ "cli_elapsed_ms_total": 9569.88,
21
+ "sql_execution_elapsed_ms_total": 15.89,
22
+ "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_0a968753a30776d8/cli/conversation.jsonl",
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+ "note": "Executed through a local AI CLI with structured usage metadata."
24
+ }
25
+ }
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_0a968753a30776d8/cli/sql_attempt_1.metadata.json ADDED
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1
+ {
2
+ "attempt": 1,
3
+ "phase": "sql_generation",
4
+ "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
5
+ "started_at": "2026-05-19T16:03:31.927839+00:00",
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+ "ended_at": "2026-05-19T16:03:41.497748+00:00",
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+ "elapsed_ms": 9569.88,
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+ "prompt_metrics": {
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+ "chars": 5947,
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+ "bytes_utf8": 5947,
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+ "lines": 180,
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+ "estimated_tokens": null
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+ },
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+ "stdout_metrics": {
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+ "chars": 788,
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+ "bytes_utf8": 788,
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+ "lines": 4,
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+ "estimated_tokens": null
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+ },
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+ "stderr_metrics": {
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+ "chars": 0,
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+ "bytes_utf8": 0,
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+ "lines": 0,
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+ "estimated_tokens": null
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+ },
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+ "parsed_output": {
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+ "format": "jsonl_events",
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+ "text_metrics": {
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+ "chars": 426,
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+ "bytes_utf8": 426,
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+ "lines": 1,
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+ "estimated_tokens": null
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+ },
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+ "usage": {
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+ "input_tokens": 13807,
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+ "cached_input_tokens": 12032,
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+ "output_tokens": 424,
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+ "reasoning_output_tokens": 309
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+ }
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+ },
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+ "prompt_path": "cli/sql_prompt_attempt_1.txt",
42
+ "response_path": "cli/sql_response_attempt_1.txt",
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+ "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
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+ "stderr_path": "cli/sql_stderr_attempt_1.txt"
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+ }
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_0a968753a30776d8/cli/sql_prompt_attempt_1.txt ADDED
@@ -0,0 +1,180 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ You are generating one SQLite SELECT query for a single-table SQL QA task.
2
+ Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
3
+ Rules:
4
+ - Use only the provided table and columns.
5
+ - Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
6
+ - Prefer the planned template and bound roles when provided.
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+ - Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
8
+ - Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
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+ - Quote identifiers with double quotes.
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+ - Return no markdown and no extra prose.
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+
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+ Dataset context:
13
+ Dataset context for SQL QA:
14
+ - dataset_id: c20
15
+ - dataset_name: C20
16
+ - table_name: c20
17
+ - table_layout: single-table dataset (do not assume joins).
18
+ - row_semantics: One row is one tabular observation with 6 feature columns and target `class`.
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+ - task_type: classification
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+ - target_column: class
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+ - main_row_count: 44819
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+ - important_fields:
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+ - white_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 strength.
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+ - white_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 file.
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+ - white_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 rank.
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+ - black_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 strength.
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+ - black_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 file.
28
+ - black_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 rank.
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+ - class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
30
+ - useful_field_combinations: [['white_piece0_strength', 'white_piece0_file', 'class'], ['white_piece0_strength', 'white_piece0_strength', 'class']]
31
+ - fields_requiring_caution: ['class']
32
+ - source_url: https://www.openml.org/d/41027
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+
34
+ SQLite schema snapshot:
35
+ {
36
+ "table_name": "c20",
37
+ "quoted_table_name": "\"c20\"",
38
+ "row_count": 44819,
39
+ "columns": [
40
+ {
41
+ "name": "white_piece0_strength",
42
+ "type": "TEXT",
43
+ "notnull": false,
44
+ "pk": false
45
+ },
46
+ {
47
+ "name": "white_piece0_file",
48
+ "type": "TEXT",
49
+ "notnull": false,
50
+ "pk": false
51
+ },
52
+ {
53
+ "name": "white_piece0_rank",
54
+ "type": "TEXT",
55
+ "notnull": false,
56
+ "pk": false
57
+ },
58
+ {
59
+ "name": "black_piece0_strength",
60
+ "type": "TEXT",
61
+ "notnull": false,
62
+ "pk": false
63
+ },
64
+ {
65
+ "name": "black_piece0_file",
66
+ "type": "TEXT",
67
+ "notnull": false,
68
+ "pk": false
69
+ },
70
+ {
71
+ "name": "black_piece0_rank",
72
+ "type": "TEXT",
73
+ "notnull": false,
74
+ "pk": false
75
+ },
76
+ {
77
+ "name": "class",
78
+ "type": "TEXT",
79
+ "notnull": false,
80
+ "pk": false
81
+ }
82
+ ],
83
+ "sample_rows": [
84
+ {
85
+ "white_piece0_strength": "0",
86
+ "white_piece0_file": "1",
87
+ "white_piece0_rank": "8",
88
+ "black_piece0_strength": "0",
89
+ "black_piece0_file": "0",
90
+ "black_piece0_rank": "8",
91
+ "class": "w"
92
+ },
93
+ {
94
+ "white_piece0_strength": "0",
95
+ "white_piece0_file": "2",
96
+ "white_piece0_rank": "8",
97
+ "black_piece0_strength": "0",
98
+ "black_piece0_file": "0",
99
+ "black_piece0_rank": "8",
100
+ "class": "w"
101
+ },
102
+ {
103
+ "white_piece0_strength": "0",
104
+ "white_piece0_file": "4",
105
+ "white_piece0_rank": "8",
106
+ "black_piece0_strength": "0",
107
+ "black_piece0_file": "0",
108
+ "black_piece0_rank": "8",
109
+ "class": "w"
110
+ },
111
+ {
112
+ "white_piece0_strength": "0",
113
+ "white_piece0_file": "5",
114
+ "white_piece0_rank": "8",
115
+ "black_piece0_strength": "0",
116
+ "black_piece0_file": "0",
117
+ "black_piece0_rank": "8",
118
+ "class": "w"
119
+ },
120
+ {
121
+ "white_piece0_strength": "0",
122
+ "white_piece0_file": "6",
123
+ "white_piece0_rank": "8",
124
+ "black_piece0_strength": "0",
125
+ "black_piece0_file": "0",
126
+ "black_piece0_rank": "8",
127
+ "class": "w"
128
+ }
129
+ ]
130
+ }
131
+
132
+ Shortlisted templates:
133
+ [
134
+ {
135
+ "template_id": "tpl_h2o_group_sum",
136
+ "template_name": "Grouped Numeric Sum",
137
+ "primary_family": "subgroup_structure",
138
+ "portability": "partial",
139
+ "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
140
+ "required_roles": [
141
+ "group_col",
142
+ "measure_col"
143
+ ]
144
+ }
145
+ ]
146
+
147
+ Problem instance:
148
+ {
149
+ "dataset_id": "c20",
150
+ "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=white_piece0_file, measure_col=white_piece0_file.",
151
+ "planned_template_id": "tpl_h2o_group_sum",
152
+ "bindings": {
153
+ "group_col": "white_piece0_file",
154
+ "measure_col": "white_piece0_file",
155
+ "top_k": 11,
156
+ "top_n": 4,
157
+ "num_tiles": 10,
158
+ "percentile_value": 0.9,
159
+ "z_threshold": 2.0,
160
+ "fraction_threshold": 0.1,
161
+ "baseline_multiplier": 1.5,
162
+ "baseline_fraction": 0.1,
163
+ "min_group_size": 5,
164
+ "min_support": 5,
165
+ "measure_threshold": 5.0,
166
+ "time_grain": "month",
167
+ "lookback_rows": 3,
168
+ "current_period_start": "'2024-01-01'",
169
+ "current_period_end": "'2024-04-01'",
170
+ "previous_period_start": "'2023-10-01'",
171
+ "previous_period_end": "'2024-01-01'",
172
+ "drift_ratio_threshold": 0.8
173
+ },
174
+ "can_vary": [],
175
+ "must_fix": [],
176
+ "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;"
177
+ }
178
+
179
+ Repair context:
180
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_0a968753a30776d8/cli/sql_response_attempt_1.raw.txt ADDED
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1
+ {"type":"thread.started","thread_id":"019e40fa-64e7-7121-a31f-18882d970047"}
2
+ {"type":"turn.started"}
3
+ {"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"white_piece0_file\\\", SUM(CAST(\\\"white_piece0_file\\\" AS NUMERIC)) AS \\\"total_measure\\\"\\nFROM \\\"c20\\\"\\nGROUP BY \\\"white_piece0_file\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Used the planned Grouped Numeric Sum template with group_col=\\\"white_piece0_file\\\" and measure_col=\\\"white_piece0_file\\\". Added CAST to NUMERIC because the SQLite schema stores this field as TEXT.\"}"}}
4
+ {"type":"turn.completed","usage":{"input_tokens":13807,"cached_input_tokens":12032,"output_tokens":424,"reasoning_output_tokens":309}}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_0a968753a30776d8/cli/sql_response_attempt_1.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ {"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"white_piece0_file\", SUM(CAST(\"white_piece0_file\" AS NUMERIC)) AS \"total_measure\"\nFROM \"c20\"\nGROUP BY \"white_piece0_file\"\nORDER BY \"total_measure\" DESC;","notes":"Used the planned Grouped Numeric Sum template with group_col=\"white_piece0_file\" and measure_col=\"white_piece0_file\". Added CAST to NUMERIC because the SQLite schema stores this field as TEXT."}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_0a968753a30776d8/cli/sql_stderr_attempt_1.txt ADDED
File without changes
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_attempt_1.metadata.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "attempt": 1,
3
+ "phase": "sql_generation",
4
+ "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
5
+ "started_at": "2026-05-19T16:25:41.541386+00:00",
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+ "bytes_utf8": 5919,
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+ "stdout_metrics": {
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+ "chars": 281,
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+ "bytes_utf8": 281,
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+ "lines": 4,
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+ "estimated_tokens": null
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+ "stderr_metrics": {
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+ "chars": 0,
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+ "bytes_utf8": 0,
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+ "lines": 0,
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+ "estimated_tokens": null
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+ },
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+ "parsed_output": {
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+ "format": "jsonl_events",
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+ "text_metrics": {
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+ "chars": 280,
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+ "bytes_utf8": 280,
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+ "lines": 4,
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+ "estimated_tokens": null
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+ },
35
+ "usage": {}
36
+ },
37
+ "status": "failed",
38
+ "error": "AI CLI command failed with exit code 1: ",
39
+ "prompt_path": "cli/sql_prompt_attempt_1.txt",
40
+ "response_path": "cli/sql_response_attempt_1.txt",
41
+ "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
42
+ "stderr_path": "cli/sql_stderr_attempt_1.txt"
43
+ }
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_attempt_2.metadata.json ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "attempt": 2,
3
+ "phase": "sql_generation",
4
+ "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
5
+ "started_at": "2026-05-19T16:25:45.855066+00:00",
6
+ "ended_at": "2026-05-19T16:25:49.466906+00:00",
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+ "elapsed_ms": 3611.79,
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+ "returncode": 1,
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+ "prompt_metrics": {
10
+ "chars": 5919,
11
+ "bytes_utf8": 5919,
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+ "lines": 178,
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+ "estimated_tokens": null
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+ "stdout_metrics": {
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+ "chars": 281,
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+ "bytes_utf8": 281,
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+ "lines": 4,
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+ "estimated_tokens": null
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+ },
21
+ "stderr_metrics": {
22
+ "chars": 0,
23
+ "bytes_utf8": 0,
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+ "lines": 0,
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+ "estimated_tokens": null
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+ },
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+ "parsed_output": {
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+ "text_metrics": {
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+ "bytes_utf8": 280,
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+ "lines": 4,
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+ "estimated_tokens": null
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+ },
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+ "usage": {}
36
+ },
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+ "status": "failed",
38
+ "error": "AI CLI command failed with exit code 1: ",
39
+ "prompt_path": "cli/sql_prompt_attempt_2.txt",
40
+ "response_path": "cli/sql_response_attempt_2.txt",
41
+ "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
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+ "stderr_path": "cli/sql_stderr_attempt_2.txt"
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+ }
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_prompt_attempt_1.txt ADDED
@@ -0,0 +1,178 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ You are generating one SQLite SELECT query for a single-table SQL QA task.
2
+ Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
3
+ Rules:
4
+ - Use only the provided table and columns.
5
+ - Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
6
+ - Prefer the planned template and bound roles when provided.
7
+ - Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
8
+ - Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
9
+ - Quote identifiers with double quotes.
10
+ - Return no markdown and no extra prose.
11
+
12
+ Dataset context:
13
+ Dataset context for SQL QA:
14
+ - dataset_id: c20
15
+ - dataset_name: C20
16
+ - table_name: c20
17
+ - table_layout: single-table dataset (do not assume joins).
18
+ - row_semantics: One row is one tabular observation with 6 feature columns and target `class`.
19
+ - task_type: classification
20
+ - target_column: class
21
+ - main_row_count: 44819
22
+ - important_fields:
23
+ - white_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 strength.
24
+ - white_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 file.
25
+ - white_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 rank.
26
+ - black_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 strength.
27
+ - black_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 file.
28
+ - black_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 rank.
29
+ - class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
30
+ - useful_field_combinations: [['white_piece0_strength', 'white_piece0_file', 'class'], ['white_piece0_strength', 'white_piece0_strength', 'class']]
31
+ - fields_requiring_caution: ['class']
32
+ - source_url: https://www.openml.org/d/41027
33
+
34
+ SQLite schema snapshot:
35
+ {
36
+ "table_name": "c20",
37
+ "quoted_table_name": "\"c20\"",
38
+ "row_count": 44819,
39
+ "columns": [
40
+ {
41
+ "name": "white_piece0_strength",
42
+ "type": "TEXT",
43
+ "notnull": false,
44
+ "pk": false
45
+ },
46
+ {
47
+ "name": "white_piece0_file",
48
+ "type": "TEXT",
49
+ "notnull": false,
50
+ "pk": false
51
+ },
52
+ {
53
+ "name": "white_piece0_rank",
54
+ "type": "TEXT",
55
+ "notnull": false,
56
+ "pk": false
57
+ },
58
+ {
59
+ "name": "black_piece0_strength",
60
+ "type": "TEXT",
61
+ "notnull": false,
62
+ "pk": false
63
+ },
64
+ {
65
+ "name": "black_piece0_file",
66
+ "type": "TEXT",
67
+ "notnull": false,
68
+ "pk": false
69
+ },
70
+ {
71
+ "name": "black_piece0_rank",
72
+ "type": "TEXT",
73
+ "notnull": false,
74
+ "pk": false
75
+ },
76
+ {
77
+ "name": "class",
78
+ "type": "TEXT",
79
+ "notnull": false,
80
+ "pk": false
81
+ }
82
+ ],
83
+ "sample_rows": [
84
+ {
85
+ "white_piece0_strength": "0",
86
+ "white_piece0_file": "1",
87
+ "white_piece0_rank": "8",
88
+ "black_piece0_strength": "0",
89
+ "black_piece0_file": "0",
90
+ "black_piece0_rank": "8",
91
+ "class": "w"
92
+ },
93
+ {
94
+ "white_piece0_strength": "0",
95
+ "white_piece0_file": "2",
96
+ "white_piece0_rank": "8",
97
+ "black_piece0_strength": "0",
98
+ "black_piece0_file": "0",
99
+ "black_piece0_rank": "8",
100
+ "class": "w"
101
+ },
102
+ {
103
+ "white_piece0_strength": "0",
104
+ "white_piece0_file": "4",
105
+ "white_piece0_rank": "8",
106
+ "black_piece0_strength": "0",
107
+ "black_piece0_file": "0",
108
+ "black_piece0_rank": "8",
109
+ "class": "w"
110
+ },
111
+ {
112
+ "white_piece0_strength": "0",
113
+ "white_piece0_file": "5",
114
+ "white_piece0_rank": "8",
115
+ "black_piece0_strength": "0",
116
+ "black_piece0_file": "0",
117
+ "black_piece0_rank": "8",
118
+ "class": "w"
119
+ },
120
+ {
121
+ "white_piece0_strength": "0",
122
+ "white_piece0_file": "6",
123
+ "white_piece0_rank": "8",
124
+ "black_piece0_strength": "0",
125
+ "black_piece0_file": "0",
126
+ "black_piece0_rank": "8",
127
+ "class": "w"
128
+ }
129
+ ]
130
+ }
131
+
132
+ Shortlisted templates:
133
+ [
134
+ {
135
+ "template_id": "tpl_tail_low_support_group_count_v2",
136
+ "template_name": "Low-Support Group Count",
137
+ "primary_family": "tail_rarity_structure",
138
+ "portability": "yes",
139
+ "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};",
140
+ "required_roles": [
141
+ "group_col"
142
+ ]
143
+ }
144
+ ]
145
+
146
+ Problem instance:
147
+ {
148
+ "dataset_id": "c20",
149
+ "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=black_piece0_file.",
150
+ "planned_template_id": "tpl_tail_low_support_group_count_v2",
151
+ "bindings": {
152
+ "group_col": "black_piece0_file",
153
+ "top_k": 13,
154
+ "top_n": 6,
155
+ "num_tiles": 10,
156
+ "percentile_value": 0.9,
157
+ "z_threshold": 2.0,
158
+ "fraction_threshold": 0.1,
159
+ "baseline_multiplier": 1.5,
160
+ "baseline_fraction": 0.1,
161
+ "min_group_size": 5,
162
+ "min_support": 5,
163
+ "measure_threshold": 6.0,
164
+ "time_grain": "month",
165
+ "lookback_rows": 3,
166
+ "current_period_start": "'2024-01-01'",
167
+ "current_period_end": "'2024-04-01'",
168
+ "previous_period_start": "'2023-10-01'",
169
+ "previous_period_end": "'2024-01-01'",
170
+ "drift_ratio_threshold": 0.8
171
+ },
172
+ "can_vary": [],
173
+ "must_fix": [],
174
+ "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};"
175
+ }
176
+
177
+ Repair context:
178
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_prompt_attempt_2.txt ADDED
@@ -0,0 +1,178 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ You are generating one SQLite SELECT query for a single-table SQL QA task.
2
+ Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
3
+ Rules:
4
+ - Use only the provided table and columns.
5
+ - Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
6
+ - Prefer the planned template and bound roles when provided.
7
+ - Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
8
+ - Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
9
+ - Quote identifiers with double quotes.
10
+ - Return no markdown and no extra prose.
11
+
12
+ Dataset context:
13
+ Dataset context for SQL QA:
14
+ - dataset_id: c20
15
+ - dataset_name: C20
16
+ - table_name: c20
17
+ - table_layout: single-table dataset (do not assume joins).
18
+ - row_semantics: One row is one tabular observation with 6 feature columns and target `class`.
19
+ - task_type: classification
20
+ - target_column: class
21
+ - main_row_count: 44819
22
+ - important_fields:
23
+ - white_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 strength.
24
+ - white_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 file.
25
+ - white_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 rank.
26
+ - black_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 strength.
27
+ - black_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 file.
28
+ - black_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 rank.
29
+ - class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
30
+ - useful_field_combinations: [['white_piece0_strength', 'white_piece0_file', 'class'], ['white_piece0_strength', 'white_piece0_strength', 'class']]
31
+ - fields_requiring_caution: ['class']
32
+ - source_url: https://www.openml.org/d/41027
33
+
34
+ SQLite schema snapshot:
35
+ {
36
+ "table_name": "c20",
37
+ "quoted_table_name": "\"c20\"",
38
+ "row_count": 44819,
39
+ "columns": [
40
+ {
41
+ "name": "white_piece0_strength",
42
+ "type": "TEXT",
43
+ "notnull": false,
44
+ "pk": false
45
+ },
46
+ {
47
+ "name": "white_piece0_file",
48
+ "type": "TEXT",
49
+ "notnull": false,
50
+ "pk": false
51
+ },
52
+ {
53
+ "name": "white_piece0_rank",
54
+ "type": "TEXT",
55
+ "notnull": false,
56
+ "pk": false
57
+ },
58
+ {
59
+ "name": "black_piece0_strength",
60
+ "type": "TEXT",
61
+ "notnull": false,
62
+ "pk": false
63
+ },
64
+ {
65
+ "name": "black_piece0_file",
66
+ "type": "TEXT",
67
+ "notnull": false,
68
+ "pk": false
69
+ },
70
+ {
71
+ "name": "black_piece0_rank",
72
+ "type": "TEXT",
73
+ "notnull": false,
74
+ "pk": false
75
+ },
76
+ {
77
+ "name": "class",
78
+ "type": "TEXT",
79
+ "notnull": false,
80
+ "pk": false
81
+ }
82
+ ],
83
+ "sample_rows": [
84
+ {
85
+ "white_piece0_strength": "0",
86
+ "white_piece0_file": "1",
87
+ "white_piece0_rank": "8",
88
+ "black_piece0_strength": "0",
89
+ "black_piece0_file": "0",
90
+ "black_piece0_rank": "8",
91
+ "class": "w"
92
+ },
93
+ {
94
+ "white_piece0_strength": "0",
95
+ "white_piece0_file": "2",
96
+ "white_piece0_rank": "8",
97
+ "black_piece0_strength": "0",
98
+ "black_piece0_file": "0",
99
+ "black_piece0_rank": "8",
100
+ "class": "w"
101
+ },
102
+ {
103
+ "white_piece0_strength": "0",
104
+ "white_piece0_file": "4",
105
+ "white_piece0_rank": "8",
106
+ "black_piece0_strength": "0",
107
+ "black_piece0_file": "0",
108
+ "black_piece0_rank": "8",
109
+ "class": "w"
110
+ },
111
+ {
112
+ "white_piece0_strength": "0",
113
+ "white_piece0_file": "5",
114
+ "white_piece0_rank": "8",
115
+ "black_piece0_strength": "0",
116
+ "black_piece0_file": "0",
117
+ "black_piece0_rank": "8",
118
+ "class": "w"
119
+ },
120
+ {
121
+ "white_piece0_strength": "0",
122
+ "white_piece0_file": "6",
123
+ "white_piece0_rank": "8",
124
+ "black_piece0_strength": "0",
125
+ "black_piece0_file": "0",
126
+ "black_piece0_rank": "8",
127
+ "class": "w"
128
+ }
129
+ ]
130
+ }
131
+
132
+ Shortlisted templates:
133
+ [
134
+ {
135
+ "template_id": "tpl_tail_low_support_group_count_v2",
136
+ "template_name": "Low-Support Group Count",
137
+ "primary_family": "tail_rarity_structure",
138
+ "portability": "yes",
139
+ "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};",
140
+ "required_roles": [
141
+ "group_col"
142
+ ]
143
+ }
144
+ ]
145
+
146
+ Problem instance:
147
+ {
148
+ "dataset_id": "c20",
149
+ "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=black_piece0_file.",
150
+ "planned_template_id": "tpl_tail_low_support_group_count_v2",
151
+ "bindings": {
152
+ "group_col": "black_piece0_file",
153
+ "top_k": 13,
154
+ "top_n": 6,
155
+ "num_tiles": 10,
156
+ "percentile_value": 0.9,
157
+ "z_threshold": 2.0,
158
+ "fraction_threshold": 0.1,
159
+ "baseline_multiplier": 1.5,
160
+ "baseline_fraction": 0.1,
161
+ "min_group_size": 5,
162
+ "min_support": 5,
163
+ "measure_threshold": 6.0,
164
+ "time_grain": "month",
165
+ "lookback_rows": 3,
166
+ "current_period_start": "'2024-01-01'",
167
+ "current_period_end": "'2024-04-01'",
168
+ "previous_period_start": "'2023-10-01'",
169
+ "previous_period_end": "'2024-01-01'",
170
+ "drift_ratio_threshold": 0.8
171
+ },
172
+ "can_vary": [],
173
+ "must_fix": [],
174
+ "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};"
175
+ }
176
+
177
+ Repair context:
178
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_response_attempt_1.raw.txt ADDED
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+ {"type":"turn.started"}
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+ {"type":"error","message":"Quota exceeded. Check your plan and billing details."}
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+ {"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_response_attempt_2.raw.txt ADDED
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2
+ {"type":"turn.started"}
3
+ {"type":"error","message":"Quota exceeded. Check your plan and billing details."}
4
+ {"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_response_attempt_2.txt ADDED
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+ {"type":"thread.started","thread_id":"019e410e-bff2-7bc3-9384-9c1e1433fca8"}
2
+ {"type":"turn.started"}
3
+ {"type":"error","message":"Quota exceeded. Check your plan and billing details."}
4
+ {"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1a518b5407c04d6c/cli/sql_stderr_attempt_1.txt ADDED
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File without changes
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1
+ {
2
+ "attempt": 1,
3
+ "phase": "sql_generation",
4
+ "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
5
+ "started_at": "2026-05-19T16:27:58.764057+00:00",
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+ },
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+ "usage": {}
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+ },
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+ "status": "failed",
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+ "error": "AI CLI command failed with exit code 1: ",
39
+ "prompt_path": "cli/sql_prompt_attempt_1.txt",
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+ "response_path": "cli/sql_response_attempt_1.txt",
41
+ "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
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+ "stderr_path": "cli/sql_stderr_attempt_1.txt"
43
+ }
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1ef2d9144d994e4b/cli/sql_attempt_2.metadata.json ADDED
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1
+ {
2
+ "attempt": 2,
3
+ "phase": "sql_generation",
4
+ "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
5
+ "started_at": "2026-05-19T16:28:03.134317+00:00",
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+ },
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+ "status": "failed",
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+ "error": "AI CLI command failed with exit code 1: ",
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+ "prompt_path": "cli/sql_prompt_attempt_2.txt",
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+ "response_path": "cli/sql_response_attempt_2.txt",
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+ "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
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+ }
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1ef2d9144d994e4b/cli/sql_prompt_attempt_1.txt ADDED
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1
+ You are generating one SQLite SELECT query for a single-table SQL QA task.
2
+ Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
3
+ Rules:
4
+ - Use only the provided table and columns.
5
+ - Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
6
+ - Prefer the planned template and bound roles when provided.
7
+ - Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
8
+ - Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
9
+ - Quote identifiers with double quotes.
10
+ - Return no markdown and no extra prose.
11
+
12
+ Dataset context:
13
+ Dataset context for SQL QA:
14
+ - dataset_id: c20
15
+ - dataset_name: C20
16
+ - table_name: c20
17
+ - table_layout: single-table dataset (do not assume joins).
18
+ - row_semantics: One row is one tabular observation with 6 feature columns and target `class`.
19
+ - task_type: classification
20
+ - target_column: class
21
+ - main_row_count: 44819
22
+ - important_fields:
23
+ - white_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 strength.
24
+ - white_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 file.
25
+ - white_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 rank.
26
+ - black_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 strength.
27
+ - black_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 file.
28
+ - black_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 rank.
29
+ - class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
30
+ - useful_field_combinations: [['white_piece0_strength', 'white_piece0_file', 'class'], ['white_piece0_strength', 'white_piece0_strength', 'class']]
31
+ - fields_requiring_caution: ['class']
32
+ - source_url: https://www.openml.org/d/41027
33
+
34
+ SQLite schema snapshot:
35
+ {
36
+ "table_name": "c20",
37
+ "quoted_table_name": "\"c20\"",
38
+ "row_count": 44819,
39
+ "columns": [
40
+ {
41
+ "name": "white_piece0_strength",
42
+ "type": "TEXT",
43
+ "notnull": false,
44
+ "pk": false
45
+ },
46
+ {
47
+ "name": "white_piece0_file",
48
+ "type": "TEXT",
49
+ "notnull": false,
50
+ "pk": false
51
+ },
52
+ {
53
+ "name": "white_piece0_rank",
54
+ "type": "TEXT",
55
+ "notnull": false,
56
+ "pk": false
57
+ },
58
+ {
59
+ "name": "black_piece0_strength",
60
+ "type": "TEXT",
61
+ "notnull": false,
62
+ "pk": false
63
+ },
64
+ {
65
+ "name": "black_piece0_file",
66
+ "type": "TEXT",
67
+ "notnull": false,
68
+ "pk": false
69
+ },
70
+ {
71
+ "name": "black_piece0_rank",
72
+ "type": "TEXT",
73
+ "notnull": false,
74
+ "pk": false
75
+ },
76
+ {
77
+ "name": "class",
78
+ "type": "TEXT",
79
+ "notnull": false,
80
+ "pk": false
81
+ }
82
+ ],
83
+ "sample_rows": [
84
+ {
85
+ "white_piece0_strength": "0",
86
+ "white_piece0_file": "1",
87
+ "white_piece0_rank": "8",
88
+ "black_piece0_strength": "0",
89
+ "black_piece0_file": "0",
90
+ "black_piece0_rank": "8",
91
+ "class": "w"
92
+ },
93
+ {
94
+ "white_piece0_strength": "0",
95
+ "white_piece0_file": "2",
96
+ "white_piece0_rank": "8",
97
+ "black_piece0_strength": "0",
98
+ "black_piece0_file": "0",
99
+ "black_piece0_rank": "8",
100
+ "class": "w"
101
+ },
102
+ {
103
+ "white_piece0_strength": "0",
104
+ "white_piece0_file": "4",
105
+ "white_piece0_rank": "8",
106
+ "black_piece0_strength": "0",
107
+ "black_piece0_file": "0",
108
+ "black_piece0_rank": "8",
109
+ "class": "w"
110
+ },
111
+ {
112
+ "white_piece0_strength": "0",
113
+ "white_piece0_file": "5",
114
+ "white_piece0_rank": "8",
115
+ "black_piece0_strength": "0",
116
+ "black_piece0_file": "0",
117
+ "black_piece0_rank": "8",
118
+ "class": "w"
119
+ },
120
+ {
121
+ "white_piece0_strength": "0",
122
+ "white_piece0_file": "6",
123
+ "white_piece0_rank": "8",
124
+ "black_piece0_strength": "0",
125
+ "black_piece0_file": "0",
126
+ "black_piece0_rank": "8",
127
+ "class": "w"
128
+ }
129
+ ]
130
+ }
131
+
132
+ Shortlisted templates:
133
+ [
134
+ {
135
+ "template_id": "tpl_m4_window_partition_avg",
136
+ "template_name": "Window Partition Average",
137
+ "primary_family": "conditional_dependency_structure",
138
+ "portability": "partial",
139
+ "sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
140
+ "required_roles": [
141
+ "group_col",
142
+ "measure_col"
143
+ ]
144
+ }
145
+ ]
146
+
147
+ Problem instance:
148
+ {
149
+ "dataset_id": "c20",
150
+ "question": "Use template Window Partition Average to probe direction_consistency with semantic role filtered_stable_view. Focus on group_col=white_piece0_rank, measure_col=black_piece0_strength.",
151
+ "planned_template_id": "tpl_m4_window_partition_avg",
152
+ "bindings": {
153
+ "group_col": "white_piece0_rank",
154
+ "measure_col": "black_piece0_strength",
155
+ "top_k": 15,
156
+ "top_n": 7,
157
+ "num_tiles": 10,
158
+ "percentile_value": 0.95,
159
+ "z_threshold": 2.0,
160
+ "fraction_threshold": 0.05,
161
+ "baseline_multiplier": 1.75,
162
+ "baseline_fraction": 0.1,
163
+ "min_group_size": 5,
164
+ "min_support": 4,
165
+ "measure_threshold": 6.0,
166
+ "time_grain": "month",
167
+ "lookback_rows": 3,
168
+ "current_period_start": "'2024-01-01'",
169
+ "current_period_end": "'2024-04-01'",
170
+ "previous_period_start": "'2023-10-01'",
171
+ "previous_period_end": "'2024-01-01'",
172
+ "drift_ratio_threshold": 0.8
173
+ },
174
+ "can_vary": [],
175
+ "must_fix": [],
176
+ "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
177
+ }
178
+
179
+ Repair context:
180
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_1ef2d9144d994e4b/cli/sql_prompt_attempt_2.txt ADDED
@@ -0,0 +1,180 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ You are generating one SQLite SELECT query for a single-table SQL QA task.
2
+ Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
3
+ Rules:
4
+ - Use only the provided table and columns.
5
+ - Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
6
+ - Prefer the planned template and bound roles when provided.
7
+ - Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
8
+ - Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
9
+ - Quote identifiers with double quotes.
10
+ - Return no markdown and no extra prose.
11
+
12
+ Dataset context:
13
+ Dataset context for SQL QA:
14
+ - dataset_id: c20
15
+ - dataset_name: C20
16
+ - table_name: c20
17
+ - table_layout: single-table dataset (do not assume joins).
18
+ - row_semantics: One row is one tabular observation with 6 feature columns and target `class`.
19
+ - task_type: classification
20
+ - target_column: class
21
+ - main_row_count: 44819
22
+ - important_fields:
23
+ - white_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 strength.
24
+ - white_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 file.
25
+ - white_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 rank.
26
+ - black_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 strength.
27
+ - black_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 file.
28
+ - black_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 rank.
29
+ - class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
30
+ - useful_field_combinations: [['white_piece0_strength', 'white_piece0_file', 'class'], ['white_piece0_strength', 'white_piece0_strength', 'class']]
31
+ - fields_requiring_caution: ['class']
32
+ - source_url: https://www.openml.org/d/41027
33
+
34
+ SQLite schema snapshot:
35
+ {
36
+ "table_name": "c20",
37
+ "quoted_table_name": "\"c20\"",
38
+ "row_count": 44819,
39
+ "columns": [
40
+ {
41
+ "name": "white_piece0_strength",
42
+ "type": "TEXT",
43
+ "notnull": false,
44
+ "pk": false
45
+ },
46
+ {
47
+ "name": "white_piece0_file",
48
+ "type": "TEXT",
49
+ "notnull": false,
50
+ "pk": false
51
+ },
52
+ {
53
+ "name": "white_piece0_rank",
54
+ "type": "TEXT",
55
+ "notnull": false,
56
+ "pk": false
57
+ },
58
+ {
59
+ "name": "black_piece0_strength",
60
+ "type": "TEXT",
61
+ "notnull": false,
62
+ "pk": false
63
+ },
64
+ {
65
+ "name": "black_piece0_file",
66
+ "type": "TEXT",
67
+ "notnull": false,
68
+ "pk": false
69
+ },
70
+ {
71
+ "name": "black_piece0_rank",
72
+ "type": "TEXT",
73
+ "notnull": false,
74
+ "pk": false
75
+ },
76
+ {
77
+ "name": "class",
78
+ "type": "TEXT",
79
+ "notnull": false,
80
+ "pk": false
81
+ }
82
+ ],
83
+ "sample_rows": [
84
+ {
85
+ "white_piece0_strength": "0",
86
+ "white_piece0_file": "1",
87
+ "white_piece0_rank": "8",
88
+ "black_piece0_strength": "0",
89
+ "black_piece0_file": "0",
90
+ "black_piece0_rank": "8",
91
+ "class": "w"
92
+ },
93
+ {
94
+ "white_piece0_strength": "0",
95
+ "white_piece0_file": "2",
96
+ "white_piece0_rank": "8",
97
+ "black_piece0_strength": "0",
98
+ "black_piece0_file": "0",
99
+ "black_piece0_rank": "8",
100
+ "class": "w"
101
+ },
102
+ {
103
+ "white_piece0_strength": "0",
104
+ "white_piece0_file": "4",
105
+ "white_piece0_rank": "8",
106
+ "black_piece0_strength": "0",
107
+ "black_piece0_file": "0",
108
+ "black_piece0_rank": "8",
109
+ "class": "w"
110
+ },
111
+ {
112
+ "white_piece0_strength": "0",
113
+ "white_piece0_file": "5",
114
+ "white_piece0_rank": "8",
115
+ "black_piece0_strength": "0",
116
+ "black_piece0_file": "0",
117
+ "black_piece0_rank": "8",
118
+ "class": "w"
119
+ },
120
+ {
121
+ "white_piece0_strength": "0",
122
+ "white_piece0_file": "6",
123
+ "white_piece0_rank": "8",
124
+ "black_piece0_strength": "0",
125
+ "black_piece0_file": "0",
126
+ "black_piece0_rank": "8",
127
+ "class": "w"
128
+ }
129
+ ]
130
+ }
131
+
132
+ Shortlisted templates:
133
+ [
134
+ {
135
+ "template_id": "tpl_m4_window_partition_avg",
136
+ "template_name": "Window Partition Average",
137
+ "primary_family": "conditional_dependency_structure",
138
+ "portability": "partial",
139
+ "sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;",
140
+ "required_roles": [
141
+ "group_col",
142
+ "measure_col"
143
+ ]
144
+ }
145
+ ]
146
+
147
+ Problem instance:
148
+ {
149
+ "dataset_id": "c20",
150
+ "question": "Use template Window Partition Average to probe direction_consistency with semantic role filtered_stable_view. Focus on group_col=white_piece0_rank, measure_col=black_piece0_strength.",
151
+ "planned_template_id": "tpl_m4_window_partition_avg",
152
+ "bindings": {
153
+ "group_col": "white_piece0_rank",
154
+ "measure_col": "black_piece0_strength",
155
+ "top_k": 15,
156
+ "top_n": 7,
157
+ "num_tiles": 10,
158
+ "percentile_value": 0.95,
159
+ "z_threshold": 2.0,
160
+ "fraction_threshold": 0.05,
161
+ "baseline_multiplier": 1.75,
162
+ "baseline_fraction": 0.1,
163
+ "min_group_size": 5,
164
+ "min_support": 4,
165
+ "measure_threshold": 6.0,
166
+ "time_grain": "month",
167
+ "lookback_rows": 3,
168
+ "current_period_start": "'2024-01-01'",
169
+ "current_period_end": "'2024-04-01'",
170
+ "previous_period_start": "'2023-10-01'",
171
+ "previous_period_end": "'2024-01-01'",
172
+ "drift_ratio_threshold": 0.8
173
+ },
174
+ "can_vary": [],
175
+ "must_fix": [],
176
+ "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;"
177
+ }
178
+
179
+ Repair context:
180
+ {}
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+ "phase": "sql_generation",
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+ "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
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+ "response_path": "cli/sql_response_attempt_1.txt",
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+ {
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+ "phase": "sql_generation",
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+ "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
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Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_25608dad21edeaa5/cli/sql_prompt_attempt_1.txt ADDED
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1
+ You are generating one SQLite SELECT query for a single-table SQL QA task.
2
+ Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
3
+ Rules:
4
+ - Use only the provided table and columns.
5
+ - Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
6
+ - Prefer the planned template and bound roles when provided.
7
+ - Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
8
+ - Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
9
+ - Quote identifiers with double quotes.
10
+ - Return no markdown and no extra prose.
11
+
12
+ Dataset context:
13
+ Dataset context for SQL QA:
14
+ - dataset_id: c20
15
+ - dataset_name: C20
16
+ - table_name: c20
17
+ - table_layout: single-table dataset (do not assume joins).
18
+ - row_semantics: One row is one tabular observation with 6 feature columns and target `class`.
19
+ - task_type: classification
20
+ - target_column: class
21
+ - main_row_count: 44819
22
+ - important_fields:
23
+ - white_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 strength.
24
+ - white_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 file.
25
+ - white_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 rank.
26
+ - black_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 strength.
27
+ - black_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 file.
28
+ - black_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 rank.
29
+ - class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
30
+ - useful_field_combinations: [['white_piece0_strength', 'white_piece0_file', 'class'], ['white_piece0_strength', 'white_piece0_strength', 'class']]
31
+ - fields_requiring_caution: ['class']
32
+ - source_url: https://www.openml.org/d/41027
33
+
34
+ SQLite schema snapshot:
35
+ {
36
+ "table_name": "c20",
37
+ "quoted_table_name": "\"c20\"",
38
+ "row_count": 44819,
39
+ "columns": [
40
+ {
41
+ "name": "white_piece0_strength",
42
+ "type": "TEXT",
43
+ "notnull": false,
44
+ "pk": false
45
+ },
46
+ {
47
+ "name": "white_piece0_file",
48
+ "type": "TEXT",
49
+ "notnull": false,
50
+ "pk": false
51
+ },
52
+ {
53
+ "name": "white_piece0_rank",
54
+ "type": "TEXT",
55
+ "notnull": false,
56
+ "pk": false
57
+ },
58
+ {
59
+ "name": "black_piece0_strength",
60
+ "type": "TEXT",
61
+ "notnull": false,
62
+ "pk": false
63
+ },
64
+ {
65
+ "name": "black_piece0_file",
66
+ "type": "TEXT",
67
+ "notnull": false,
68
+ "pk": false
69
+ },
70
+ {
71
+ "name": "black_piece0_rank",
72
+ "type": "TEXT",
73
+ "notnull": false,
74
+ "pk": false
75
+ },
76
+ {
77
+ "name": "class",
78
+ "type": "TEXT",
79
+ "notnull": false,
80
+ "pk": false
81
+ }
82
+ ],
83
+ "sample_rows": [
84
+ {
85
+ "white_piece0_strength": "0",
86
+ "white_piece0_file": "1",
87
+ "white_piece0_rank": "8",
88
+ "black_piece0_strength": "0",
89
+ "black_piece0_file": "0",
90
+ "black_piece0_rank": "8",
91
+ "class": "w"
92
+ },
93
+ {
94
+ "white_piece0_strength": "0",
95
+ "white_piece0_file": "2",
96
+ "white_piece0_rank": "8",
97
+ "black_piece0_strength": "0",
98
+ "black_piece0_file": "0",
99
+ "black_piece0_rank": "8",
100
+ "class": "w"
101
+ },
102
+ {
103
+ "white_piece0_strength": "0",
104
+ "white_piece0_file": "4",
105
+ "white_piece0_rank": "8",
106
+ "black_piece0_strength": "0",
107
+ "black_piece0_file": "0",
108
+ "black_piece0_rank": "8",
109
+ "class": "w"
110
+ },
111
+ {
112
+ "white_piece0_strength": "0",
113
+ "white_piece0_file": "5",
114
+ "white_piece0_rank": "8",
115
+ "black_piece0_strength": "0",
116
+ "black_piece0_file": "0",
117
+ "black_piece0_rank": "8",
118
+ "class": "w"
119
+ },
120
+ {
121
+ "white_piece0_strength": "0",
122
+ "white_piece0_file": "6",
123
+ "white_piece0_rank": "8",
124
+ "black_piece0_strength": "0",
125
+ "black_piece0_file": "0",
126
+ "black_piece0_rank": "8",
127
+ "class": "w"
128
+ }
129
+ ]
130
+ }
131
+
132
+ Shortlisted templates:
133
+ [
134
+ {
135
+ "template_id": "tpl_m4_group_condition_rate",
136
+ "template_name": "Grouped Condition Rate",
137
+ "primary_family": "conditional_dependency_structure",
138
+ "portability": "yes",
139
+ "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
140
+ "required_roles": [
141
+ "group_col",
142
+ "condition_col"
143
+ ]
144
+ }
145
+ ]
146
+
147
+ Problem instance:
148
+ {
149
+ "dataset_id": "c20",
150
+ "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=white_piece0_rank, condition_col=white_piece0_strength.",
151
+ "planned_template_id": "tpl_m4_group_condition_rate",
152
+ "bindings": {
153
+ "group_col": "white_piece0_rank",
154
+ "condition_col": "white_piece0_strength",
155
+ "condition_value": "6",
156
+ "positive_value": "0",
157
+ "negative_value": "6",
158
+ "top_k": 15,
159
+ "top_n": 4,
160
+ "num_tiles": 10,
161
+ "percentile_value": 0.9,
162
+ "z_threshold": 2.0,
163
+ "fraction_threshold": 0.05,
164
+ "baseline_multiplier": 1.75,
165
+ "baseline_fraction": 0.1,
166
+ "min_group_size": 5,
167
+ "min_support": 4,
168
+ "measure_threshold": 5.0,
169
+ "time_grain": "month",
170
+ "lookback_rows": 3,
171
+ "current_period_start": "'2024-01-01'",
172
+ "current_period_end": "'2024-04-01'",
173
+ "previous_period_start": "'2023-10-01'",
174
+ "previous_period_end": "'2024-01-01'",
175
+ "drift_ratio_threshold": 0.8
176
+ },
177
+ "can_vary": [],
178
+ "must_fix": [],
179
+ "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
180
+ }
181
+
182
+ Repair context:
183
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_25608dad21edeaa5/cli/sql_prompt_attempt_2.txt ADDED
@@ -0,0 +1,183 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ You are generating one SQLite SELECT query for a single-table SQL QA task.
2
+ Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
3
+ Rules:
4
+ - Use only the provided table and columns.
5
+ - Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
6
+ - Prefer the planned template and bound roles when provided.
7
+ - Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
8
+ - Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
9
+ - Quote identifiers with double quotes.
10
+ - Return no markdown and no extra prose.
11
+
12
+ Dataset context:
13
+ Dataset context for SQL QA:
14
+ - dataset_id: c20
15
+ - dataset_name: C20
16
+ - table_name: c20
17
+ - table_layout: single-table dataset (do not assume joins).
18
+ - row_semantics: One row is one tabular observation with 6 feature columns and target `class`.
19
+ - task_type: classification
20
+ - target_column: class
21
+ - main_row_count: 44819
22
+ - important_fields:
23
+ - white_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 strength.
24
+ - white_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 file.
25
+ - white_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 rank.
26
+ - black_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 strength.
27
+ - black_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 file.
28
+ - black_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 rank.
29
+ - class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
30
+ - useful_field_combinations: [['white_piece0_strength', 'white_piece0_file', 'class'], ['white_piece0_strength', 'white_piece0_strength', 'class']]
31
+ - fields_requiring_caution: ['class']
32
+ - source_url: https://www.openml.org/d/41027
33
+
34
+ SQLite schema snapshot:
35
+ {
36
+ "table_name": "c20",
37
+ "quoted_table_name": "\"c20\"",
38
+ "row_count": 44819,
39
+ "columns": [
40
+ {
41
+ "name": "white_piece0_strength",
42
+ "type": "TEXT",
43
+ "notnull": false,
44
+ "pk": false
45
+ },
46
+ {
47
+ "name": "white_piece0_file",
48
+ "type": "TEXT",
49
+ "notnull": false,
50
+ "pk": false
51
+ },
52
+ {
53
+ "name": "white_piece0_rank",
54
+ "type": "TEXT",
55
+ "notnull": false,
56
+ "pk": false
57
+ },
58
+ {
59
+ "name": "black_piece0_strength",
60
+ "type": "TEXT",
61
+ "notnull": false,
62
+ "pk": false
63
+ },
64
+ {
65
+ "name": "black_piece0_file",
66
+ "type": "TEXT",
67
+ "notnull": false,
68
+ "pk": false
69
+ },
70
+ {
71
+ "name": "black_piece0_rank",
72
+ "type": "TEXT",
73
+ "notnull": false,
74
+ "pk": false
75
+ },
76
+ {
77
+ "name": "class",
78
+ "type": "TEXT",
79
+ "notnull": false,
80
+ "pk": false
81
+ }
82
+ ],
83
+ "sample_rows": [
84
+ {
85
+ "white_piece0_strength": "0",
86
+ "white_piece0_file": "1",
87
+ "white_piece0_rank": "8",
88
+ "black_piece0_strength": "0",
89
+ "black_piece0_file": "0",
90
+ "black_piece0_rank": "8",
91
+ "class": "w"
92
+ },
93
+ {
94
+ "white_piece0_strength": "0",
95
+ "white_piece0_file": "2",
96
+ "white_piece0_rank": "8",
97
+ "black_piece0_strength": "0",
98
+ "black_piece0_file": "0",
99
+ "black_piece0_rank": "8",
100
+ "class": "w"
101
+ },
102
+ {
103
+ "white_piece0_strength": "0",
104
+ "white_piece0_file": "4",
105
+ "white_piece0_rank": "8",
106
+ "black_piece0_strength": "0",
107
+ "black_piece0_file": "0",
108
+ "black_piece0_rank": "8",
109
+ "class": "w"
110
+ },
111
+ {
112
+ "white_piece0_strength": "0",
113
+ "white_piece0_file": "5",
114
+ "white_piece0_rank": "8",
115
+ "black_piece0_strength": "0",
116
+ "black_piece0_file": "0",
117
+ "black_piece0_rank": "8",
118
+ "class": "w"
119
+ },
120
+ {
121
+ "white_piece0_strength": "0",
122
+ "white_piece0_file": "6",
123
+ "white_piece0_rank": "8",
124
+ "black_piece0_strength": "0",
125
+ "black_piece0_file": "0",
126
+ "black_piece0_rank": "8",
127
+ "class": "w"
128
+ }
129
+ ]
130
+ }
131
+
132
+ Shortlisted templates:
133
+ [
134
+ {
135
+ "template_id": "tpl_m4_group_condition_rate",
136
+ "template_name": "Grouped Condition Rate",
137
+ "primary_family": "conditional_dependency_structure",
138
+ "portability": "yes",
139
+ "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;",
140
+ "required_roles": [
141
+ "group_col",
142
+ "condition_col"
143
+ ]
144
+ }
145
+ ]
146
+
147
+ Problem instance:
148
+ {
149
+ "dataset_id": "c20",
150
+ "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=white_piece0_rank, condition_col=white_piece0_strength.",
151
+ "planned_template_id": "tpl_m4_group_condition_rate",
152
+ "bindings": {
153
+ "group_col": "white_piece0_rank",
154
+ "condition_col": "white_piece0_strength",
155
+ "condition_value": "6",
156
+ "positive_value": "0",
157
+ "negative_value": "6",
158
+ "top_k": 15,
159
+ "top_n": 4,
160
+ "num_tiles": 10,
161
+ "percentile_value": 0.9,
162
+ "z_threshold": 2.0,
163
+ "fraction_threshold": 0.05,
164
+ "baseline_multiplier": 1.75,
165
+ "baseline_fraction": 0.1,
166
+ "min_group_size": 5,
167
+ "min_support": 4,
168
+ "measure_threshold": 5.0,
169
+ "time_grain": "month",
170
+ "lookback_rows": 3,
171
+ "current_period_start": "'2024-01-01'",
172
+ "current_period_end": "'2024-04-01'",
173
+ "previous_period_start": "'2023-10-01'",
174
+ "previous_period_end": "'2024-01-01'",
175
+ "drift_ratio_threshold": 0.8
176
+ },
177
+ "can_vary": [],
178
+ "must_fix": [],
179
+ "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;"
180
+ }
181
+
182
+ Repair context:
183
+ {}
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+ {"type":"turn.started"}
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+ {"type":"error","message":"Quota exceeded. Check your plan and billing details."}
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+ {"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
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+ {"type":"turn.started"}
3
+ {"type":"error","message":"Quota exceeded. Check your plan and billing details."}
4
+ {"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_25608dad21edeaa5/cli/sql_stderr_attempt_1.txt ADDED
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Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_25608dad21edeaa5/cli/sql_stderr_attempt_2.txt ADDED
File without changes
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+ {
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+ "attempt": 1,
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+ "phase": "sql_generation",
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+ "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
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+ "started_at": "2026-05-19T16:16:18.607824+00:00",
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+ "parsed_output": {
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+ "format": "jsonl_events",
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+ },
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+ "status": "failed",
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+ "error": "AI CLI command failed with exit code 1: ",
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+ "prompt_path": "cli/sql_prompt_attempt_1.txt",
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+ "response_path": "cli/sql_response_attempt_1.txt",
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+ "raw_response_path": "cli/sql_response_attempt_1.raw.txt",
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+ "stderr_path": "cli/sql_stderr_attempt_1.txt"
43
+ }
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_3c72e3519211cdf0/cli/sql_attempt_2.metadata.json ADDED
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+ {
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+ "attempt": 2,
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+ "phase": "sql_generation",
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+ "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -",
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+ "status": "failed",
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+ "error": "AI CLI command failed with exit code 1: ",
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+ "prompt_path": "cli/sql_prompt_attempt_2.txt",
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+ "response_path": "cli/sql_response_attempt_2.txt",
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+ "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
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Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_3c72e3519211cdf0/cli/sql_prompt_attempt_1.txt ADDED
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1
+ You are generating one SQLite SELECT query for a single-table SQL QA task.
2
+ Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
3
+ Rules:
4
+ - Use only the provided table and columns.
5
+ - Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
6
+ - Prefer the planned template and bound roles when provided.
7
+ - Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
8
+ - Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
9
+ - Quote identifiers with double quotes.
10
+ - Return no markdown and no extra prose.
11
+
12
+ Dataset context:
13
+ Dataset context for SQL QA:
14
+ - dataset_id: c20
15
+ - dataset_name: C20
16
+ - table_name: c20
17
+ - table_layout: single-table dataset (do not assume joins).
18
+ - row_semantics: One row is one tabular observation with 6 feature columns and target `class`.
19
+ - task_type: classification
20
+ - target_column: class
21
+ - main_row_count: 44819
22
+ - important_fields:
23
+ - white_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 strength.
24
+ - white_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 file.
25
+ - white_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 rank.
26
+ - black_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 strength.
27
+ - black_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 file.
28
+ - black_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 rank.
29
+ - class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
30
+ - useful_field_combinations: [['white_piece0_strength', 'white_piece0_file', 'class'], ['white_piece0_strength', 'white_piece0_strength', 'class']]
31
+ - fields_requiring_caution: ['class']
32
+ - source_url: https://www.openml.org/d/41027
33
+
34
+ SQLite schema snapshot:
35
+ {
36
+ "table_name": "c20",
37
+ "quoted_table_name": "\"c20\"",
38
+ "row_count": 44819,
39
+ "columns": [
40
+ {
41
+ "name": "white_piece0_strength",
42
+ "type": "TEXT",
43
+ "notnull": false,
44
+ "pk": false
45
+ },
46
+ {
47
+ "name": "white_piece0_file",
48
+ "type": "TEXT",
49
+ "notnull": false,
50
+ "pk": false
51
+ },
52
+ {
53
+ "name": "white_piece0_rank",
54
+ "type": "TEXT",
55
+ "notnull": false,
56
+ "pk": false
57
+ },
58
+ {
59
+ "name": "black_piece0_strength",
60
+ "type": "TEXT",
61
+ "notnull": false,
62
+ "pk": false
63
+ },
64
+ {
65
+ "name": "black_piece0_file",
66
+ "type": "TEXT",
67
+ "notnull": false,
68
+ "pk": false
69
+ },
70
+ {
71
+ "name": "black_piece0_rank",
72
+ "type": "TEXT",
73
+ "notnull": false,
74
+ "pk": false
75
+ },
76
+ {
77
+ "name": "class",
78
+ "type": "TEXT",
79
+ "notnull": false,
80
+ "pk": false
81
+ }
82
+ ],
83
+ "sample_rows": [
84
+ {
85
+ "white_piece0_strength": "0",
86
+ "white_piece0_file": "1",
87
+ "white_piece0_rank": "8",
88
+ "black_piece0_strength": "0",
89
+ "black_piece0_file": "0",
90
+ "black_piece0_rank": "8",
91
+ "class": "w"
92
+ },
93
+ {
94
+ "white_piece0_strength": "0",
95
+ "white_piece0_file": "2",
96
+ "white_piece0_rank": "8",
97
+ "black_piece0_strength": "0",
98
+ "black_piece0_file": "0",
99
+ "black_piece0_rank": "8",
100
+ "class": "w"
101
+ },
102
+ {
103
+ "white_piece0_strength": "0",
104
+ "white_piece0_file": "4",
105
+ "white_piece0_rank": "8",
106
+ "black_piece0_strength": "0",
107
+ "black_piece0_file": "0",
108
+ "black_piece0_rank": "8",
109
+ "class": "w"
110
+ },
111
+ {
112
+ "white_piece0_strength": "0",
113
+ "white_piece0_file": "5",
114
+ "white_piece0_rank": "8",
115
+ "black_piece0_strength": "0",
116
+ "black_piece0_file": "0",
117
+ "black_piece0_rank": "8",
118
+ "class": "w"
119
+ },
120
+ {
121
+ "white_piece0_strength": "0",
122
+ "white_piece0_file": "6",
123
+ "white_piece0_rank": "8",
124
+ "black_piece0_strength": "0",
125
+ "black_piece0_file": "0",
126
+ "black_piece0_rank": "8",
127
+ "class": "w"
128
+ }
129
+ ]
130
+ }
131
+
132
+ Shortlisted templates:
133
+ [
134
+ {
135
+ "template_id": "tpl_tpch_relative_total_threshold",
136
+ "template_name": "Relative-to-Total Extreme Threshold",
137
+ "primary_family": "tail_rarity_structure",
138
+ "portability": "partial",
139
+ "sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
140
+ "required_roles": [
141
+ "group_col",
142
+ "measure_col"
143
+ ]
144
+ }
145
+ ]
146
+
147
+ Problem instance:
148
+ {
149
+ "dataset_id": "c20",
150
+ "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=white_piece0_rank, measure_col=white_piece0_file.",
151
+ "planned_template_id": "tpl_tpch_relative_total_threshold",
152
+ "bindings": {
153
+ "group_col": "white_piece0_rank",
154
+ "measure_col": "white_piece0_file",
155
+ "top_k": 19,
156
+ "top_n": 7,
157
+ "num_tiles": 10,
158
+ "percentile_value": 0.95,
159
+ "z_threshold": 2.0,
160
+ "fraction_threshold": 0.05,
161
+ "baseline_multiplier": 1.75,
162
+ "baseline_fraction": 0.1,
163
+ "min_group_size": 5,
164
+ "min_support": 4,
165
+ "measure_threshold": 4.0,
166
+ "time_grain": "month",
167
+ "lookback_rows": 3,
168
+ "current_period_start": "'2024-01-01'",
169
+ "current_period_end": "'2024-04-01'",
170
+ "previous_period_start": "'2023-10-01'",
171
+ "previous_period_end": "'2024-01-01'",
172
+ "drift_ratio_threshold": 0.8
173
+ },
174
+ "can_vary": [],
175
+ "must_fix": [],
176
+ "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;"
177
+ }
178
+
179
+ Repair context:
180
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_3c72e3519211cdf0/cli/sql_prompt_attempt_2.txt ADDED
@@ -0,0 +1,180 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ You are generating one SQLite SELECT query for a single-table SQL QA task.
2
+ Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
3
+ Rules:
4
+ - Use only the provided table and columns.
5
+ - Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
6
+ - Prefer the planned template and bound roles when provided.
7
+ - Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
8
+ - Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
9
+ - Quote identifiers with double quotes.
10
+ - Return no markdown and no extra prose.
11
+
12
+ Dataset context:
13
+ Dataset context for SQL QA:
14
+ - dataset_id: c20
15
+ - dataset_name: C20
16
+ - table_name: c20
17
+ - table_layout: single-table dataset (do not assume joins).
18
+ - row_semantics: One row is one tabular observation with 6 feature columns and target `class`.
19
+ - task_type: classification
20
+ - target_column: class
21
+ - main_row_count: 44819
22
+ - important_fields:
23
+ - white_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 strength.
24
+ - white_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 file.
25
+ - white_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 rank.
26
+ - black_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 strength.
27
+ - black_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 file.
28
+ - black_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 rank.
29
+ - class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
30
+ - useful_field_combinations: [['white_piece0_strength', 'white_piece0_file', 'class'], ['white_piece0_strength', 'white_piece0_strength', 'class']]
31
+ - fields_requiring_caution: ['class']
32
+ - source_url: https://www.openml.org/d/41027
33
+
34
+ SQLite schema snapshot:
35
+ {
36
+ "table_name": "c20",
37
+ "quoted_table_name": "\"c20\"",
38
+ "row_count": 44819,
39
+ "columns": [
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+ {
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+ "name": "white_piece0_strength",
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+ "type": "TEXT",
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+ "notnull": false,
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+ "pk": false
45
+ },
46
+ {
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+ "name": "white_piece0_file",
48
+ "type": "TEXT",
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+ "notnull": false,
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+ "pk": false
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+ },
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+ {
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+ "name": "white_piece0_rank",
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+ "type": "TEXT",
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+ "notnull": false,
56
+ "pk": false
57
+ },
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+ {
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+ "name": "black_piece0_strength",
60
+ "type": "TEXT",
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+ "notnull": false,
62
+ "pk": false
63
+ },
64
+ {
65
+ "name": "black_piece0_file",
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+ "type": "TEXT",
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+ "notnull": false,
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+ "pk": false
69
+ },
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+ {
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+ "name": "black_piece0_rank",
72
+ "type": "TEXT",
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+ "notnull": false,
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+ "pk": false
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+ },
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+ {
77
+ "name": "class",
78
+ "type": "TEXT",
79
+ "notnull": false,
80
+ "pk": false
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+ }
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+ ],
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+ "sample_rows": [
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+ {
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+ "white_piece0_strength": "0",
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+ "white_piece0_file": "1",
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+ "white_piece0_rank": "8",
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+ "black_piece0_strength": "0",
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+ "black_piece0_file": "0",
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+ "black_piece0_rank": "8",
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+ "class": "w"
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+ },
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+ {
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+ "white_piece0_strength": "0",
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+ "white_piece0_file": "2",
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+ "white_piece0_rank": "8",
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+ "black_piece0_strength": "0",
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+ "black_piece0_file": "0",
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+ "black_piece0_rank": "8",
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+ "class": "w"
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+ },
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+ {
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+ "white_piece0_strength": "0",
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+ "white_piece0_file": "4",
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+ "white_piece0_rank": "8",
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+ "black_piece0_strength": "0",
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+ "black_piece0_file": "0",
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+ "black_piece0_rank": "8",
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+ "class": "w"
110
+ },
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+ {
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+ "white_piece0_strength": "0",
113
+ "white_piece0_file": "5",
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+ "white_piece0_rank": "8",
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+ "black_piece0_strength": "0",
116
+ "black_piece0_file": "0",
117
+ "black_piece0_rank": "8",
118
+ "class": "w"
119
+ },
120
+ {
121
+ "white_piece0_strength": "0",
122
+ "white_piece0_file": "6",
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+ "white_piece0_rank": "8",
124
+ "black_piece0_strength": "0",
125
+ "black_piece0_file": "0",
126
+ "black_piece0_rank": "8",
127
+ "class": "w"
128
+ }
129
+ ]
130
+ }
131
+
132
+ Shortlisted templates:
133
+ [
134
+ {
135
+ "template_id": "tpl_tpch_relative_total_threshold",
136
+ "template_name": "Relative-to-Total Extreme Threshold",
137
+ "primary_family": "tail_rarity_structure",
138
+ "portability": "partial",
139
+ "sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;",
140
+ "required_roles": [
141
+ "group_col",
142
+ "measure_col"
143
+ ]
144
+ }
145
+ ]
146
+
147
+ Problem instance:
148
+ {
149
+ "dataset_id": "c20",
150
+ "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=white_piece0_rank, measure_col=white_piece0_file.",
151
+ "planned_template_id": "tpl_tpch_relative_total_threshold",
152
+ "bindings": {
153
+ "group_col": "white_piece0_rank",
154
+ "measure_col": "white_piece0_file",
155
+ "top_k": 19,
156
+ "top_n": 7,
157
+ "num_tiles": 10,
158
+ "percentile_value": 0.95,
159
+ "z_threshold": 2.0,
160
+ "fraction_threshold": 0.05,
161
+ "baseline_multiplier": 1.75,
162
+ "baseline_fraction": 0.1,
163
+ "min_group_size": 5,
164
+ "min_support": 4,
165
+ "measure_threshold": 4.0,
166
+ "time_grain": "month",
167
+ "lookback_rows": 3,
168
+ "current_period_start": "'2024-01-01'",
169
+ "current_period_end": "'2024-04-01'",
170
+ "previous_period_start": "'2023-10-01'",
171
+ "previous_period_end": "'2024-01-01'",
172
+ "drift_ratio_threshold": 0.8
173
+ },
174
+ "can_vary": [],
175
+ "must_fix": [],
176
+ "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;"
177
+ }
178
+
179
+ Repair context:
180
+ {}
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1
+ You are generating one SQLite SELECT query for a single-table SQL QA task.
2
+ Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}.
3
+ Rules:
4
+ - Use only the provided table and columns.
5
+ - Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM.
6
+ - Prefer the planned template and bound roles when provided.
7
+ - Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
8
+ - Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
9
+ - Quote identifiers with double quotes.
10
+ - Return no markdown and no extra prose.
11
+
12
+ Dataset context:
13
+ Dataset context for SQL QA:
14
+ - dataset_id: c20
15
+ - dataset_name: C20
16
+ - table_name: c20
17
+ - table_layout: single-table dataset (do not assume joins).
18
+ - row_semantics: One row is one tabular observation with 6 feature columns and target `class`.
19
+ - task_type: classification
20
+ - target_column: class
21
+ - main_row_count: 44819
22
+ - important_fields:
23
+ - white_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 strength.
24
+ - white_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 file.
25
+ - white_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for white piece0 rank.
26
+ - black_piece0_strength: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 strength.
27
+ - black_piece0_file: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 file.
28
+ - black_piece0_rank: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for black piece0 rank.
29
+ - class: role=target, type=categorical_target. tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for class.
30
+ - useful_field_combinations: [['white_piece0_strength', 'white_piece0_file', 'class'], ['white_piece0_strength', 'white_piece0_strength', 'class']]
31
+ - fields_requiring_caution: ['class']
32
+ - source_url: https://www.openml.org/d/41027
33
+
34
+ SQLite schema snapshot:
35
+ {
36
+ "table_name": "c20",
37
+ "quoted_table_name": "\"c20\"",
38
+ "row_count": 44819,
39
+ "columns": [
40
+ {
41
+ "name": "white_piece0_strength",
42
+ "type": "TEXT",
43
+ "notnull": false,
44
+ "pk": false
45
+ },
46
+ {
47
+ "name": "white_piece0_file",
48
+ "type": "TEXT",
49
+ "notnull": false,
50
+ "pk": false
51
+ },
52
+ {
53
+ "name": "white_piece0_rank",
54
+ "type": "TEXT",
55
+ "notnull": false,
56
+ "pk": false
57
+ },
58
+ {
59
+ "name": "black_piece0_strength",
60
+ "type": "TEXT",
61
+ "notnull": false,
62
+ "pk": false
63
+ },
64
+ {
65
+ "name": "black_piece0_file",
66
+ "type": "TEXT",
67
+ "notnull": false,
68
+ "pk": false
69
+ },
70
+ {
71
+ "name": "black_piece0_rank",
72
+ "type": "TEXT",
73
+ "notnull": false,
74
+ "pk": false
75
+ },
76
+ {
77
+ "name": "class",
78
+ "type": "TEXT",
79
+ "notnull": false,
80
+ "pk": false
81
+ }
82
+ ],
83
+ "sample_rows": [
84
+ {
85
+ "white_piece0_strength": "0",
86
+ "white_piece0_file": "1",
87
+ "white_piece0_rank": "8",
88
+ "black_piece0_strength": "0",
89
+ "black_piece0_file": "0",
90
+ "black_piece0_rank": "8",
91
+ "class": "w"
92
+ },
93
+ {
94
+ "white_piece0_strength": "0",
95
+ "white_piece0_file": "2",
96
+ "white_piece0_rank": "8",
97
+ "black_piece0_strength": "0",
98
+ "black_piece0_file": "0",
99
+ "black_piece0_rank": "8",
100
+ "class": "w"
101
+ },
102
+ {
103
+ "white_piece0_strength": "0",
104
+ "white_piece0_file": "4",
105
+ "white_piece0_rank": "8",
106
+ "black_piece0_strength": "0",
107
+ "black_piece0_file": "0",
108
+ "black_piece0_rank": "8",
109
+ "class": "w"
110
+ },
111
+ {
112
+ "white_piece0_strength": "0",
113
+ "white_piece0_file": "5",
114
+ "white_piece0_rank": "8",
115
+ "black_piece0_strength": "0",
116
+ "black_piece0_file": "0",
117
+ "black_piece0_rank": "8",
118
+ "class": "w"
119
+ },
120
+ {
121
+ "white_piece0_strength": "0",
122
+ "white_piece0_file": "6",
123
+ "white_piece0_rank": "8",
124
+ "black_piece0_strength": "0",
125
+ "black_piece0_file": "0",
126
+ "black_piece0_rank": "8",
127
+ "class": "w"
128
+ }
129
+ ]
130
+ }
131
+
132
+ Shortlisted templates:
133
+ [
134
+ {
135
+ "template_id": "tpl_h2o_group_sum",
136
+ "template_name": "Grouped Numeric Sum",
137
+ "primary_family": "subgroup_structure",
138
+ "portability": "partial",
139
+ "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;",
140
+ "required_roles": [
141
+ "group_col",
142
+ "measure_col"
143
+ ]
144
+ }
145
+ ]
146
+
147
+ Problem instance:
148
+ {
149
+ "dataset_id": "c20",
150
+ "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=white_piece0_rank, measure_col=white_piece0_rank.",
151
+ "planned_template_id": "tpl_h2o_group_sum",
152
+ "bindings": {
153
+ "group_col": "white_piece0_rank",
154
+ "measure_col": "white_piece0_rank",
155
+ "top_k": 12,
156
+ "top_n": 5,
157
+ "num_tiles": 10,
158
+ "percentile_value": 0.95,
159
+ "z_threshold": 2.0,
160
+ "fraction_threshold": 0.1,
161
+ "baseline_multiplier": 1.5,
162
+ "baseline_fraction": 0.1,
163
+ "min_group_size": 5,
164
+ "min_support": 5,
165
+ "measure_threshold": 7.0,
166
+ "time_grain": "month",
167
+ "lookback_rows": 3,
168
+ "current_period_start": "'2024-01-01'",
169
+ "current_period_end": "'2024-04-01'",
170
+ "previous_period_start": "'2023-10-01'",
171
+ "previous_period_end": "'2024-01-01'",
172
+ "drift_ratio_threshold": 0.8
173
+ },
174
+ "can_vary": [],
175
+ "must_fix": [],
176
+ "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;"
177
+ }
178
+
179
+ Repair context:
180
+ {}