Triple
T35752388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 Spanish Grand Prix |
E1033350
|
entity |
| Predicate | ageOfMaxVerstappenAtVictory |
P183625
|
FINISHED |
| Object | 18 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 18 | Statement: [2016 Spanish Grand Prix, ageOfMaxVerstappenAtVictory, 18]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageOfMaxVerstappenAtVictory Context triple: [2016 Spanish Grand Prix, ageOfMaxVerstappenAtVictory, 18]
-
A.
ageAtFirstFormulaOneWin
Indicates the age a person was when they achieved their first Formula One race victory.
-
B.
ageAtF1Debut
Indicates the age a driver was when they made their debut in Formula 1.
-
C.
becameYoungestF1Driver
Indicates that a person achieved the status of being the youngest driver ever to compete in a Formula 1 race at that time.
-
D.
ageAtVictory
Indicates the age an individual or entity was when they achieved a particular victory or success.
-
E.
youngestPoleSitterAtTime
Indicates that the subject is the youngest driver ever to have started a race from pole position at the specified time.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76e1262f48190a313318665acc189 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a1f64f1081908cc2774840684310 |
completed | May 3, 2026, 7:28 p.m. |
| PD | Predicate disambiguation | batch_69f7a070e23881909a233370acb57384 |
completed | May 3, 2026, 7:22 p.m. |
| PDg | Predicate description generation | batch_69f7a162672481909773f8383d91159a |
completed | May 3, 2026, 7:26 p.m. |
Created at: May 3, 2026, 4:06 p.m.