Triple
T26461755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pierre Gasly |
E665656
|
entity |
| Predicate | tookFirstF1WinWithTeam |
P99785
|
FINISHED |
| Object | Scuderia AlphaTauri |
—
|
NE NERFINISHED |
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: Scuderia AlphaTauri | Statement: [Pierre Gasly, tookFirstF1WinWithTeam, Scuderia AlphaTauri]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tookFirstF1WinWithTeam Context triple: [Pierre Gasly, tookFirstF1WinWithTeam, Scuderia AlphaTauri]
-
A.
achievedFirstF1PodiumWith
Indicates that one entity secured their first-ever Formula 1 podium finish while driving for or in association with the other entity.
-
B.
firstFormulaOneWin
chosen
Indicates that the subject achieved their first victory in a Formula One race in relation to the specified event or context.
-
C.
ageAtFirstFormulaOneWin
Indicates the age a person was when they achieved their first Formula One race victory.
-
D.
madeF1DebutForTeam
Indicates that a driver’s first-ever Formula 1 race appearance was made while competing for the specified team.
-
E.
firstUsedForFormulaOneWorldChampionship
Indicates that something (typically a circuit, track, or venue) was used for the first time in hosting a Formula One World Championship event.
- F. None of above.
Provenance (3 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_69ee883e812c8190a9b5a9cdb87fee5e |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f612956424819083b0e451342a5811 |
completed | May 2, 2026, 3:04 p.m. |
| PD | Predicate disambiguation | batch_69f60b89cc048190a9feb24466006be0 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 27, 2026, 12:13 a.m.