gold
SELECT T2.surname
FROM qualifying AS T1
INNER JOIN drivers AS T2 ON T2.driverId = T1.driverId
WHERE T1.raceId = 19
ORDER BY T1.q2 ASC
LIMIT 1;
- T1.q2
- ascending
sha256:ea18e98d4db4d459758b36ffd9f2284f7ca53fee049312e4ef58f71d1afea4e1
R-ORD GOLD-ONLY arbitrary-cut
formula_1 · dev_20251106-00000-of-00001 from https://huggingface.co/datasets/birdsql/bird_sql_dev_20251106/resolve/3c11fb193e5439b338e23677fa0aae11e8b85db9/data/dev_20251106-00000-of-00001.json (commit 3c11fb19, downloaded 2026-09-07)
What is the surname of the driver with the best lap time in race number 19 in the second qualifying period?
the hint the set supplies: race number refers to raceId; second qualifying period refers to q2; best lap time refers to MIN(q2);
This question was audited without a prediction beside it, so there is nothing to compare the gold with. The probes below read the gold alone.
read by hand, 2026-09-07: wrong the gold does not answer its question on this data
the qualifying time is NULL in six of the 22 rows and sorts first ascending, so the gold returns a driver who set no time in that period rather than the best one
a maintainer's reading of this question, out of classification.json, copied from plans/reports/bird-dev-sqlite-260907/classification.json. It is not a verdict and nothing above it was computed from it.
SELECT T2.surname
FROM qualifying AS T1
INNER JOIN drivers AS T2 ON T2.driverId = T1.driverId
WHERE T1.raceId = 19
ORDER BY T1.q2 ASC
LIMIT 1;
sha256:ea18e98d4db4d459758b36ffd9f2284f7ca53fee049312e4ef58f71d1afea4e1
from evidence-gold.json, 1 row
| surnameTEXT |
|---|
| Fisichella |
A smell is a mechanical reason to read this gold statement again. It is a heuristic: it does not state that the statement is wrong, and a maintainer decides.
this statement orders by a text column holding only numbers, and ordering it as a number gives a different answer, so the gold may be sorting 9.5 above 10
{
"heuristic": true,
"keys": [
{
"key": "T1.q2",
"column": "qualifying.q2",
"declared_type": "TEXT",
"not_applicable": null,
"census": {
"rows": 7397,
"nulls": 3807,
"empty_strings": 23,
"non_numeric": 3567,
"pattern": "^-?[0-9]+(\\.[0-9]+)?$"
},
"every_value_is_numeric": false
}
]
}
this statement cuts its result at a LIMIT that does not decide which rows come back, so a different but equally correct statement can return other rows and score zero
from smells.json, 6 rows
| Fisichella | NULL |
| Nakajima | NULL |
| Bourdais | NULL |
| Sato | NULL |
| Sutil | NULL |
| Davidson | NULL |
{
"heuristic": true,
"cut": 1,
"offset": 0,
"distinct_kept": false,
"unbounded_sql": "SELECT T2.surname, T1.q2 AS attestql_ordering_key_0 FROM qualifying AS T1 INNER JOIN drivers AS T2 ON T2.driverId = T1.driverId WHERE T1.raceId = 19 ORDER BY T1.q2 ASC",
"unbounded_rows": 22,
"projected_columns": [
"surname"
],
"ordering_key_columns": [
"attestql_ordering_key_0"
],
"ordering_keys": [
{
"key": "T1.q2",
"direction": "asc",
"nulls": "first",
"nulls_first_in_effect": true,
"returned_rows_null_in_this_key": 1,
"fires": true
}
],
"returned_rows_with_a_null_key": [
[
{
"type": "str",
"value": "Fisichella"
}
]
],
"tied_at_the_cut": {
"positions": [
0,
1,
2,
3,
4,
5
],
"tied_rows": 6,
"distinct_projected_answers": 6,
"rows": [
[
{
"type": "str",
"value": "Fisichella"
}
],
[
{
"type": "str",
"value": "Nakajima"
}
],
[
{
"type": "str",
"value": "Bourdais"
}
],
[
{
"type": "str",
"value": "Sato"
}
],
[
{
"type": "str",
"value": "Sutil"
}
],
[
{
"type": "str",
"value": "Davidson"
}
]
]
},
"case": "tie-at-the-cut, null-first"
}
rerun over the same rows in another physical order this statement gives another answer, so its result depends on how the rows are stored and not only on the data
{
"heuristic": true,
"rule": "R-ORD",
"baseline_result_hash": "sha256:ea18e98d4db4d459758b36ffd9f2284f7ca53fee049312e4ef58f71d1afea4e1",
"baseline_result": {
"columns": [
{
"name": "surname",
"declared_type": "TEXT"
}
],
"row_count": 1,
"truncated": false,
"rows_shown": 1,
"rows": [
[
{
"type": "str",
"value": "Fisichella"
}
]
],
"result_hash": "sha256:ea18e98d4db4d459758b36ffd9f2284f7ca53fee049312e4ef58f71d1afea4e1"
},
"planner_statistics": {},
"shuffle": {
"seed": "1",
"row_limit": 300000,
"tables": [
"qualifying",
"drivers"
],
"tables_not_shuffled": [],
"tables_skipped_for_size": {
"lapTimes": 420369
},
"tables_not_reached_by_a_copy": {}
},
"shuffled_copies": {
"run": true,
"verdict": "equal",
"differs": false,
"result_hash": "sha256:ea18e98d4db4d459758b36ffd9f2284f7ca53fee049312e4ef58f71d1afea4e1",
"result": {
"columns": [
{
"name": "surname",
"declared_type": "TEXT"
}
],
"row_count": 1,
"truncated": false,
"rows_shown": 1,
"rows": [
[
{
"type": "str",
"value": "Fisichella"
}
]
],
"result_hash": "sha256:ea18e98d4db4d459758b36ffd9f2284f7ca53fee049312e4ef58f71d1afea4e1"
}
},
"plan_variant": {
"run": false,
"reason": "the plan variant was not asked for"
}
}
SELECT T2.surname
FROM qualifying AS T1
INNER JOIN drivers AS T2 ON T2.driverId = T1.driverId
WHERE T1.raceId = 19
ORDER BY T1.q2 ASC
LIMIT 1;
result_hash sha256:ea18e98d4db4d459758b36ffd9f2284f7ca53fee049312e4ef58f71d1afea4e1 recomputed from this JSON: match
record_hash sha256:de2253e49dfb989cdca066fe2f6abced4ac37a7be3ff8fa008a4723423fd2ca4 recomputed from this JSON: match
from evidence-gold.json, 1 row
| surnameTEXT |
|---|
| Fisichella |
re-run this statement read-only against SQLite 3.53.4 | file=/private/tmp/attestql-runs/data/dev/dev_databases/formula_1/formula_1.sqlite | size=22360064 under the session settings and over the data this record's fixture digest names, and compare the two results under R-ORD