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  1. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_02958ac87d4b811b/cli/sql_attempt_1.metadata.json +43 -0
  2. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_02958ac87d4b811b/cli/sql_attempt_2.metadata.json +43 -0
  3. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_02958ac87d4b811b/cli/sql_prompt_attempt_1.txt +182 -0
  4. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_02958ac87d4b811b/cli/sql_prompt_attempt_2.txt +182 -0
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  6. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_02958ac87d4b811b/cli/sql_response_attempt_1.txt +4 -0
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  9. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_02958ac87d4b811b/cli/sql_stderr_attempt_1.txt +0 -0
  10. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_02958ac87d4b811b/cli/sql_stderr_attempt_2.txt +0 -0
  11. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_04da003512687a17/cli/sql_attempt_1.metadata.json +43 -0
  12. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_04da003512687a17/cli/sql_attempt_2.metadata.json +43 -0
  13. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_04da003512687a17/cli/sql_prompt_attempt_1.txt +184 -0
  14. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_04da003512687a17/cli/sql_prompt_attempt_2.txt +184 -0
  15. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_04da003512687a17/cli/sql_response_attempt_1.raw.txt +4 -0
  16. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_04da003512687a17/cli/sql_response_attempt_1.txt +4 -0
  17. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_04da003512687a17/cli/sql_response_attempt_2.raw.txt +4 -0
  18. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_04da003512687a17/cli/sql_response_attempt_2.txt +4 -0
  19. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_04da003512687a17/cli/sql_stderr_attempt_1.txt +0 -0
  20. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_04da003512687a17/cli/sql_stderr_attempt_2.txt +0 -0
  21. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_2e56b37c13b65408/cli/sql_prompt_attempt_1.txt +178 -0
  22. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_2e56b37c13b65408/cli/sql_response_attempt_1.raw.txt +4 -0
  23. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_2e56b37c13b65408/cli/sql_response_attempt_2.raw.txt +4 -0
  24. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_2e56b37c13b65408/cli/sql_stderr_attempt_1.txt +0 -0
  25. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_429e0ba25567496b/cli/sql_attempt_1.metadata.json +43 -0
  26. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_429e0ba25567496b/cli/sql_attempt_2.metadata.json +43 -0
  27. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_429e0ba25567496b/cli/sql_prompt_attempt_1.txt +178 -0
  28. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_429e0ba25567496b/cli/sql_prompt_attempt_2.txt +178 -0
  29. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_429e0ba25567496b/cli/sql_response_attempt_1.raw.txt +4 -0
  30. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_429e0ba25567496b/cli/sql_response_attempt_1.txt +4 -0
  31. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_429e0ba25567496b/cli/sql_response_attempt_2.raw.txt +4 -0
  32. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_429e0ba25567496b/cli/sql_response_attempt_2.txt +4 -0
  33. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_429e0ba25567496b/cli/sql_stderr_attempt_1.txt +0 -0
  34. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_429e0ba25567496b/cli/sql_stderr_attempt_2.txt +0 -0
  35. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/cli/sql_attempt_1.metadata.json +43 -0
  36. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/cli/sql_attempt_2.metadata.json +43 -0
  37. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/cli/sql_prompt_attempt_1.txt +178 -0
  38. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/cli/sql_prompt_attempt_2.txt +178 -0
  39. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/cli/sql_response_attempt_1.raw.txt +4 -0
  40. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/cli/sql_response_attempt_1.txt +4 -0
  41. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/cli/sql_response_attempt_2.raw.txt +4 -0
  42. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/cli/sql_response_attempt_2.txt +4 -0
  43. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/cli/sql_stderr_attempt_1.txt +0 -0
  44. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/cli/sql_stderr_attempt_2.txt +0 -0
  45. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_94dd6c5ba9470ba5/cli/sql_attempt_1.metadata.json +43 -0
  46. Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_94dd6c5ba9470ba5/cli/sql_attempt_2.metadata.json +43 -0
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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.
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+ - Add a leading SQL comment exactly like: -- template_id: <planned_template_id>.
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+ - Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV.
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+ - Quote identifiers with double quotes.
10
+ - Return no markdown and no extra prose.
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+
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+ Dataset context:
13
+ Dataset context for SQL QA:
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+ - dataset_id: c20
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+ - dataset_name: C20
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+ - table_name: c20
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+ - table_layout: single-table dataset (do not assume joins).
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+ - 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
22
+ - 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.
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+ - 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
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_tpcds_within_group_share",
136
+ "template_name": "Within-Group Share of Total",
137
+ "primary_family": "conditional_dependency_structure",
138
+ "portability": "partial",
139
+ "sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
140
+ "required_roles": [
141
+ "group_col",
142
+ "item_col",
143
+ "measure_col"
144
+ ]
145
+ }
146
+ ]
147
+
148
+ Problem instance:
149
+ {
150
+ "dataset_id": "c20",
151
+ "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=white_piece0_rank, measure_col=white_piece0_strength.",
152
+ "planned_template_id": "tpl_tpcds_within_group_share",
153
+ "bindings": {
154
+ "group_col": "white_piece0_rank",
155
+ "measure_col": "white_piece0_strength",
156
+ "item_col": "black_piece0_strength",
157
+ "top_k": 10,
158
+ "top_n": 5,
159
+ "num_tiles": 10,
160
+ "percentile_value": 0.95,
161
+ "z_threshold": 2.0,
162
+ "fraction_threshold": 0.1,
163
+ "baseline_multiplier": 1.5,
164
+ "baseline_fraction": 0.1,
165
+ "min_group_size": 5,
166
+ "min_support": 5,
167
+ "measure_threshold": 6.0,
168
+ "time_grain": "month",
169
+ "lookback_rows": 3,
170
+ "current_period_start": "'2024-01-01'",
171
+ "current_period_end": "'2024-04-01'",
172
+ "previous_period_start": "'2023-10-01'",
173
+ "previous_period_end": "'2024-01-01'",
174
+ "drift_ratio_threshold": 0.8
175
+ },
176
+ "can_vary": [],
177
+ "must_fix": [],
178
+ "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;"
179
+ }
180
+
181
+ Repair context:
182
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_02958ac87d4b811b/cli/sql_prompt_attempt_2.txt ADDED
@@ -0,0 +1,182 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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_tpcds_within_group_share",
136
+ "template_name": "Within-Group Share of Total",
137
+ "primary_family": "conditional_dependency_structure",
138
+ "portability": "partial",
139
+ "sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;",
140
+ "required_roles": [
141
+ "group_col",
142
+ "item_col",
143
+ "measure_col"
144
+ ]
145
+ }
146
+ ]
147
+
148
+ Problem instance:
149
+ {
150
+ "dataset_id": "c20",
151
+ "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=white_piece0_rank, measure_col=white_piece0_strength.",
152
+ "planned_template_id": "tpl_tpcds_within_group_share",
153
+ "bindings": {
154
+ "group_col": "white_piece0_rank",
155
+ "measure_col": "white_piece0_strength",
156
+ "item_col": "black_piece0_strength",
157
+ "top_k": 10,
158
+ "top_n": 5,
159
+ "num_tiles": 10,
160
+ "percentile_value": 0.95,
161
+ "z_threshold": 2.0,
162
+ "fraction_threshold": 0.1,
163
+ "baseline_multiplier": 1.5,
164
+ "baseline_fraction": 0.1,
165
+ "min_group_size": 5,
166
+ "min_support": 5,
167
+ "measure_threshold": 6.0,
168
+ "time_grain": "month",
169
+ "lookback_rows": 3,
170
+ "current_period_start": "'2024-01-01'",
171
+ "current_period_end": "'2024-04-01'",
172
+ "previous_period_start": "'2023-10-01'",
173
+ "previous_period_end": "'2024-01-01'",
174
+ "drift_ratio_threshold": 0.8
175
+ },
176
+ "can_vary": [],
177
+ "must_fix": [],
178
+ "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;"
179
+ }
180
+
181
+ Repair context:
182
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_02958ac87d4b811b/cli/sql_response_attempt_1.raw.txt ADDED
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1
+ {"type":"thread.started","thread_id":"019e40ff-ce0d-74e3-80fc-08c4e7c7ca0b"}
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_02958ac87d4b811b/cli/sql_response_attempt_1.txt ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {"type":"thread.started","thread_id":"019e40ff-ce0d-74e3-80fc-08c4e7c7ca0b"}
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_02958ac87d4b811b/cli/sql_response_attempt_2.raw.txt ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {"type":"thread.started","thread_id":"019e40ff-df05-74b0-bee9-d526a3603d15"}
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_02958ac87d4b811b/cli/sql_response_attempt_2.txt ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {"type":"thread.started","thread_id":"019e40ff-df05-74b0-bee9-d526a3603d15"}
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_02958ac87d4b811b/cli/sql_stderr_attempt_1.txt ADDED
File without changes
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_02958ac87d4b811b/cli/sql_stderr_attempt_2.txt ADDED
File without changes
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_04da003512687a17/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": "2026-05-19T16:11:56.645752+00:00",
6
+ "ended_at": "2026-05-19T16:12:00.627035+00:00",
7
+ "elapsed_ms": 3981.25,
8
+ "returncode": 1,
9
+ "prompt_metrics": {
10
+ "chars": 6278,
11
+ "bytes_utf8": 6278,
12
+ "lines": 184,
13
+ "estimated_tokens": null
14
+ },
15
+ "stdout_metrics": {
16
+ "chars": 281,
17
+ "bytes_utf8": 281,
18
+ "lines": 4,
19
+ "estimated_tokens": null
20
+ },
21
+ "stderr_metrics": {
22
+ "chars": 0,
23
+ "bytes_utf8": 0,
24
+ "lines": 0,
25
+ "estimated_tokens": null
26
+ },
27
+ "parsed_output": {
28
+ "format": "jsonl_events",
29
+ "text_metrics": {
30
+ "chars": 280,
31
+ "bytes_utf8": 280,
32
+ "lines": 4,
33
+ "estimated_tokens": null
34
+ },
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_04da003512687a17/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": "2026-05-19T16:12:01.628752+00:00",
6
+ "ended_at": "2026-05-19T16:12:04.903383+00:00",
7
+ "elapsed_ms": 3274.6,
8
+ "returncode": 1,
9
+ "prompt_metrics": {
10
+ "chars": 6278,
11
+ "bytes_utf8": 6278,
12
+ "lines": 184,
13
+ "estimated_tokens": null
14
+ },
15
+ "stdout_metrics": {
16
+ "chars": 281,
17
+ "bytes_utf8": 281,
18
+ "lines": 4,
19
+ "estimated_tokens": null
20
+ },
21
+ "stderr_metrics": {
22
+ "chars": 0,
23
+ "bytes_utf8": 0,
24
+ "lines": 0,
25
+ "estimated_tokens": null
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+ },
27
+ "parsed_output": {
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+ "format": "jsonl_events",
29
+ "text_metrics": {
30
+ "chars": 280,
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+ "bytes_utf8": 280,
32
+ "lines": 4,
33
+ "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_2.txt",
40
+ "response_path": "cli/sql_response_attempt_2.txt",
41
+ "raw_response_path": "cli/sql_response_attempt_2.raw.txt",
42
+ "stderr_path": "cli/sql_stderr_attempt_2.txt"
43
+ }
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_04da003512687a17/cli/sql_prompt_attempt_1.txt ADDED
@@ -0,0 +1,184 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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_c2_filtered_group_count_2d",
136
+ "template_name": "Filtered Two-Dimensional Group Count",
137
+ "primary_family": "conditional_dependency_structure",
138
+ "portability": "yes",
139
+ "sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;",
140
+ "required_roles": [
141
+ "group_col",
142
+ "group_col_2",
143
+ "predicate_col"
144
+ ]
145
+ }
146
+ ]
147
+
148
+ Problem instance:
149
+ {
150
+ "dataset_id": "c20",
151
+ "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=white_piece0_file, group_col_2=black_piece0_strength.",
152
+ "planned_template_id": "tpl_c2_filtered_group_count_2d",
153
+ "bindings": {
154
+ "group_col": "white_piece0_file",
155
+ "group_col_2": "black_piece0_strength",
156
+ "predicate_col": "white_piece0_strength",
157
+ "predicate_op": ">=",
158
+ "predicate_value": 6.0,
159
+ "top_k": 14,
160
+ "top_n": 4,
161
+ "num_tiles": 10,
162
+ "percentile_value": 0.9,
163
+ "z_threshold": 2.0,
164
+ "fraction_threshold": 0.1,
165
+ "baseline_multiplier": 1.5,
166
+ "baseline_fraction": 0.1,
167
+ "min_group_size": 5,
168
+ "min_support": 5,
169
+ "measure_threshold": 5.0,
170
+ "time_grain": "month",
171
+ "lookback_rows": 3,
172
+ "current_period_start": "'2024-01-01'",
173
+ "current_period_end": "'2024-04-01'",
174
+ "previous_period_start": "'2023-10-01'",
175
+ "previous_period_end": "'2024-01-01'",
176
+ "drift_ratio_threshold": 0.8
177
+ },
178
+ "can_vary": [],
179
+ "must_fix": [],
180
+ "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;"
181
+ }
182
+
183
+ Repair context:
184
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_04da003512687a17/cli/sql_prompt_attempt_2.txt ADDED
@@ -0,0 +1,184 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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_c2_filtered_group_count_2d",
136
+ "template_name": "Filtered Two-Dimensional Group Count",
137
+ "primary_family": "conditional_dependency_structure",
138
+ "portability": "yes",
139
+ "sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;",
140
+ "required_roles": [
141
+ "group_col",
142
+ "group_col_2",
143
+ "predicate_col"
144
+ ]
145
+ }
146
+ ]
147
+
148
+ Problem instance:
149
+ {
150
+ "dataset_id": "c20",
151
+ "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=white_piece0_file, group_col_2=black_piece0_strength.",
152
+ "planned_template_id": "tpl_c2_filtered_group_count_2d",
153
+ "bindings": {
154
+ "group_col": "white_piece0_file",
155
+ "group_col_2": "black_piece0_strength",
156
+ "predicate_col": "white_piece0_strength",
157
+ "predicate_op": ">=",
158
+ "predicate_value": 6.0,
159
+ "top_k": 14,
160
+ "top_n": 4,
161
+ "num_tiles": 10,
162
+ "percentile_value": 0.9,
163
+ "z_threshold": 2.0,
164
+ "fraction_threshold": 0.1,
165
+ "baseline_multiplier": 1.5,
166
+ "baseline_fraction": 0.1,
167
+ "min_group_size": 5,
168
+ "min_support": 5,
169
+ "measure_threshold": 5.0,
170
+ "time_grain": "month",
171
+ "lookback_rows": 3,
172
+ "current_period_start": "'2024-01-01'",
173
+ "current_period_end": "'2024-04-01'",
174
+ "previous_period_start": "'2023-10-01'",
175
+ "previous_period_end": "'2024-01-01'",
176
+ "drift_ratio_threshold": 0.8
177
+ },
178
+ "can_vary": [],
179
+ "must_fix": [],
180
+ "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;"
181
+ }
182
+
183
+ Repair context:
184
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_04da003512687a17/cli/sql_response_attempt_1.raw.txt ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {"type":"thread.started","thread_id":"019e4102-1864-7700-ad7f-3aa79413fce1"}
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_04da003512687a17/cli/sql_response_attempt_1.txt ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {"type":"thread.started","thread_id":"019e4102-1864-7700-ad7f-3aa79413fce1"}
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_04da003512687a17/cli/sql_response_attempt_2.raw.txt ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {"type":"thread.started","thread_id":"019e4102-2bd2-79c3-8efc-2a236643641a"}
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_04da003512687a17/cli/sql_response_attempt_2.txt ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {"type":"thread.started","thread_id":"019e4102-2bd2-79c3-8efc-2a236643641a"}
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_04da003512687a17/cli/sql_stderr_attempt_1.txt ADDED
File without changes
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_04da003512687a17/cli/sql_stderr_attempt_2.txt ADDED
File without changes
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_2e56b37c13b65408/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_threshold_rarity_cdf",
136
+ "template_name": "Threshold Rarity CDF",
137
+ "primary_family": "tail_rarity_structure",
138
+ "portability": "yes",
139
+ "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};",
140
+ "required_roles": [
141
+ "measure_col"
142
+ ]
143
+ }
144
+ ]
145
+
146
+ Problem instance:
147
+ {
148
+ "dataset_id": "c20",
149
+ "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=black_piece0_file.",
150
+ "planned_template_id": "tpl_threshold_rarity_cdf",
151
+ "bindings": {
152
+ "measure_col": "black_piece0_file",
153
+ "top_k": 12,
154
+ "top_n": 3,
155
+ "num_tiles": 10,
156
+ "percentile_value": 0.95,
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": 5.0,
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 AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};"
175
+ }
176
+
177
+ Repair context:
178
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_2e56b37c13b65408/cli/sql_response_attempt_1.raw.txt ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
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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":"thread.started","thread_id":"019e410d-2c39-71a3-9c1b-ca12eeca695c"}
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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_2e56b37c13b65408/cli/sql_stderr_attempt_1.txt ADDED
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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": "2026-05-19T16:06:31.401311+00:00",
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+ "stderr_metrics": {
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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"
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+ }
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_429e0ba25567496b/cli/sql_attempt_2.metadata.json ADDED
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1
+ {
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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 -",
5
+ "started_at": "2026-05-19T16:06:35.752274+00:00",
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+ },
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+ "status": "failed",
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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_429e0ba25567496b/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_clickbench_group_count",
136
+ "template_name": "Grouped Count by Category",
137
+ "primary_family": "subgroup_structure",
138
+ "portability": "yes",
139
+ "sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;",
140
+ "required_roles": [
141
+ "group_col"
142
+ ]
143
+ }
144
+ ]
145
+
146
+ Problem instance:
147
+ {
148
+ "dataset_id": "c20",
149
+ "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=white_piece0_rank.",
150
+ "planned_template_id": "tpl_clickbench_group_count",
151
+ "bindings": {
152
+ "group_col": "white_piece0_rank",
153
+ "top_k": 11,
154
+ "top_n": 3,
155
+ "num_tiles": 10,
156
+ "percentile_value": 0.95,
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": 5.0,
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 {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;"
175
+ }
176
+
177
+ Repair context:
178
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_429e0ba25567496b/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_clickbench_group_count",
136
+ "template_name": "Grouped Count by Category",
137
+ "primary_family": "subgroup_structure",
138
+ "portability": "yes",
139
+ "sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;",
140
+ "required_roles": [
141
+ "group_col"
142
+ ]
143
+ }
144
+ ]
145
+
146
+ Problem instance:
147
+ {
148
+ "dataset_id": "c20",
149
+ "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=white_piece0_rank.",
150
+ "planned_template_id": "tpl_clickbench_group_count",
151
+ "bindings": {
152
+ "group_col": "white_piece0_rank",
153
+ "top_k": 11,
154
+ "top_n": 3,
155
+ "num_tiles": 10,
156
+ "percentile_value": 0.95,
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": 5.0,
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 {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;"
175
+ }
176
+
177
+ Repair context:
178
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_429e0ba25567496b/cli/sql_response_attempt_1.raw.txt ADDED
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1
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Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_429e0ba25567496b/cli/sql_stderr_attempt_1.txt ADDED
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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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+ "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"
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+ }
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/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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Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/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_m4_quantile_tail_slice",
136
+ "template_name": "Quantile Tail Slice",
137
+ "primary_family": "tail_rarity_structure",
138
+ "portability": "partial",
139
+ "sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;",
140
+ "required_roles": [
141
+ "measure_col"
142
+ ]
143
+ }
144
+ ]
145
+
146
+ Problem instance:
147
+ {
148
+ "dataset_id": "c20",
149
+ "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=white_piece0_file.",
150
+ "planned_template_id": "tpl_m4_quantile_tail_slice",
151
+ "bindings": {
152
+ "measure_col": "white_piece0_file",
153
+ "top_k": 11,
154
+ "top_n": 4,
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": 5.0,
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": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;"
175
+ }
176
+
177
+ Repair context:
178
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/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_m4_quantile_tail_slice",
136
+ "template_name": "Quantile Tail Slice",
137
+ "primary_family": "tail_rarity_structure",
138
+ "portability": "partial",
139
+ "sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;",
140
+ "required_roles": [
141
+ "measure_col"
142
+ ]
143
+ }
144
+ ]
145
+
146
+ Problem instance:
147
+ {
148
+ "dataset_id": "c20",
149
+ "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=white_piece0_file.",
150
+ "planned_template_id": "tpl_m4_quantile_tail_slice",
151
+ "bindings": {
152
+ "measure_col": "white_piece0_file",
153
+ "top_k": 11,
154
+ "top_n": 4,
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": 5.0,
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": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;"
175
+ }
176
+
177
+ Repair context:
178
+ {}
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/cli/sql_response_attempt_1.raw.txt ADDED
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Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/cli/sql_response_attempt_1.txt ADDED
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+ {"type":"turn.started"}
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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":"thread.started","thread_id":"019e4103-3f77-7312-98f1-23c085656d09"}
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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_6303b19db8496508/cli/sql_stderr_attempt_1.txt ADDED
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Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_6303b19db8496508/cli/sql_stderr_attempt_2.txt ADDED
File without changes
Query/sql/v2/runs/v2_cli_20260502_081223_e/c20/artifacts/v2q_c20_94dd6c5ba9470ba5/cli/sql_attempt_1.metadata.json ADDED
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1
+ {
2
+ "attempt": 1,
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+ "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": "2026-05-19T16:26:29.150630+00:00",
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+ "stderr_metrics": {
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+ "bytes_utf8": 0,
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+ },
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+ "parsed_output": {
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+ "format": "jsonl_events",
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+ "bytes_utf8": 280,
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+ "lines": 4,
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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",
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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_94dd6c5ba9470ba5/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": "2026-05-19T16:26:33.365634+00:00",
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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: ",
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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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+ "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_94dd6c5ba9470ba5/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_set_consistency with semantic role rare_extreme_view. Focus on group_col=white_piece0_strength.",
150
+ "planned_template_id": "tpl_tail_low_support_group_count_v2",
151
+ "bindings": {
152
+ "group_col": "white_piece0_strength",
153
+ "top_k": 11,
154
+ "top_n": 5,
155
+ "num_tiles": 10,
156
+ "percentile_value": 0.95,
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_94dd6c5ba9470ba5/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_set_consistency with semantic role rare_extreme_view. Focus on group_col=white_piece0_strength.",
150
+ "planned_template_id": "tpl_tail_low_support_group_count_v2",
151
+ "bindings": {
152
+ "group_col": "white_piece0_strength",
153
+ "top_k": 11,
154
+ "top_n": 5,
155
+ "num_tiles": 10,
156
+ "percentile_value": 0.95,
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_94dd6c5ba9470ba5/cli/sql_response_attempt_1.raw.txt ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {"type":"thread.started","thread_id":"019e410f-6940-7f10-a634-6e846b77e576"}
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_94dd6c5ba9470ba5/cli/sql_response_attempt_1.txt ADDED
@@ -0,0 +1,4 @@
 
 
 
 
 
1
+ {"type":"thread.started","thread_id":"019e410f-6940-7f10-a634-6e846b77e576"}
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."}}