R-SET GOLD-ONLY duplicate-full-row
student_club · 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)
State what kind of expenses that Sacha Harrison incurred?
the hint the set supplies: kind of expenses refers to expense_description; Sacha Harrison is the full name; full name refers to first_name, last_name;
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.
SELECT T2.expense_description FROM member AS T1 INNER JOIN expense AS T2 ON T1.member_id = T2.link_to_member WHERE T1.first_name = 'Sacha' AND T1.last_name = 'Harrison'this statement states no ordering of its own
sha256:2aa1a006800459e357c504e76199d29a2f11ffc4251d53f9124ca31e4027c4ba
from evidence-gold.json, 12 rows
| expense_descriptionTEXT |
|---|
| Post Cards, Posters |
| Posters |
| Water, chips, cookies |
| Posters |
| Water, chips, cookies |
| Pizza |
| Water, chips, cookies |
| Travel Mug |
| Alumni Glass |
| Posters |
| Travel Mug |
| Bakery - Donuts, muffins |
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
the statement states no top level ORDER BY
{
"heuristic": true,
"reason": "the statement states no top level ORDER BY"
}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
the statement states no LIMIT
{
"heuristic": true,
"reason": "the statement states no LIMIT"
}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-SET",
"baseline_result_hash": "sha256:2aa1a006800459e357c504e76199d29a2f11ffc4251d53f9124ca31e4027c4ba",
"baseline_result": {
"columns": [
{
"name": "expense_description",
"declared_type": "TEXT"
}
],
"row_count": 12,
"truncated": false,
"rows_shown": 10,
"rows": [
[
{
"type": "str",
"value": "Post Cards, Posters"
}
],
[
{
"type": "str",
"value": "Posters"
}
],
[
{
"type": "str",
"value": "Water, chips, cookies"
}
],
[
{
"type": "str",
"value": "Posters"
}
],
[
{
"type": "str",
"value": "Water, chips, cookies"
}
],
[
{
"type": "str",
"value": "Pizza"
}
],
[
{
"type": "str",
"value": "Water, chips, cookies"
}
],
[
{
"type": "str",
"value": "Travel Mug"
}
],
[
{
"type": "str",
"value": "Alumni Glass"
}
],
[
{
"type": "str",
"value": "Posters"
}
]
],
"result_hash": "sha256:2aa1a006800459e357c504e76199d29a2f11ffc4251d53f9124ca31e4027c4ba"
},
"planner_statistics": {},
"shuffle": {
"seed": "1",
"row_limit": 300000,
"tables": [
"member",
"expense"
],
"tables_not_shuffled": [],
"tables_skipped_for_size": {},
"tables_not_reached_by_a_copy": {}
},
"shuffled_copies": {
"run": true,
"verdict": "equal",
"differs": false,
"result_hash": "sha256:1dc1a7b86d25708063b201323734f4766c7b5b145d39a236b1e7d99e64e31f6f",
"result": {
"columns": [
{
"name": "expense_description",
"declared_type": "TEXT"
}
],
"row_count": 12,
"truncated": false,
"rows_shown": 10,
"rows": [
[
{
"type": "str",
"value": "Alumni Glass"
}
],
[
{
"type": "str",
"value": "Bakery - Donuts, muffins"
}
],
[
{
"type": "str",
"value": "Pizza"
}
],
[
{
"type": "str",
"value": "Post Cards, Posters"
}
],
[
{
"type": "str",
"value": "Posters"
}
],
[
{
"type": "str",
"value": "Posters"
}
],
[
{
"type": "str",
"value": "Posters"
}
],
[
{
"type": "str",
"value": "Travel Mug"
}
],
[
{
"type": "str",
"value": "Travel Mug"
}
],
[
{
"type": "str",
"value": "Water, chips, cookies"
}
]
],
"result_hash": "sha256:1dc1a7b86d25708063b201323734f4766c7b5b145d39a236b1e7d99e64e31f6f"
}
},
"plan_variant": {
"run": false,
"reason": "the plan variant was not asked for"
}
}this statement returns the same whole row more than once and never says DISTINCT, so a statement answering the same question once per row disagrees on multiplicity alone
from smells.json, 3 rows
| Posters |
| Water, chips, cookies |
| Travel Mug |
{
"heuristic": true,
"rows": 12,
"distinct_rows": 7,
"repeated_rows": 3,
"largest_repeat": 3,
"result_bounded": false,
"distinct_stated": false,
"set_operation": false,
"repeats_of_the_rows_shown": [
3,
3,
2
]
}SELECT T2.expense_description FROM member AS T1 INNER JOIN expense AS T2 ON T1.member_id = T2.link_to_member WHERE T1.first_name = 'Sacha' AND T1.last_name = 'Harrison'result_hash sha256:2aa1a006800459e357c504e76199d29a2f11ffc4251d53f9124ca31e4027c4ba recomputed from this JSON: match
record_hash sha256:3ab645e90ead8cfe6843bb146f2a361d7a9ec3a5beff2cfaef8417b83a4ab215 recomputed from this JSON: match
from evidence-gold.json, 12 rows
| expense_descriptionTEXT |
|---|
| Post Cards, Posters |
| Posters |
| Water, chips, cookies |
| Posters |
| Water, chips, cookies |
| Pizza |
| Water, chips, cookies |
| Travel Mug |
| Alumni Glass |
| Posters |
| Travel Mug |
| Bakery - Donuts, muffins |
re-run this statement read-only against SQLite 3.53.4 | file=/private/tmp/attestql-runs/data/dev/dev_databases/student_club/student_club.sqlite | size=2641920 under the session settings and over the data this record's fixture digest names, and compare the two results under R-SET