Triple
T17723630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max Verstappen |
E442402
|
entity |
| Predicate | becameYoungestGrandPrixWinner |
P128739
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Max Verstappen, becameYoungestGrandPrixWinner, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: becameYoungestGrandPrixWinner Context triple: [Max Verstappen, becameYoungestGrandPrixWinner, true]
-
A.
ageAtFirstFormulaOneWin
Indicates the age a person was when they achieved their first Formula One race victory.
-
B.
firstMotoGPWin
Indicates that the event or race represents the first MotoGP victory achieved by the specified rider.
-
C.
wasYoungestHeadOfState
Indicates that the subject held the position of head of state at a time when they were younger than any other person who had ever held that role up to that point.
-
D.
madeMotoGPDebut
Indicates that an entity participated in its first MotoGP race or event.
-
E.
grandPrixDebutYear
Indicates the year in which an entity first participated in a Grand Prix event.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4748900608190bf5ba04415edaffc |
completed | April 19, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69e3cde815e08190881972e2d80d151e |
completed | April 18, 2026, 6:31 p.m. |
| PDg | Predicate description generation | batch_69e3d37ab6988190bd326ea6f8dd4aaa |
completed | April 18, 2026, 6:54 p.m. |
Created at: April 10, 2026, 10:07 a.m.