Triple
T28991240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nico Hülkenberg |
E736029
|
entity |
| Predicate | LeMansWinningTeam |
P63067
|
FINISHED |
| Object | Porsche Team |
—
|
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: Porsche Team | Statement: [Nico Hülkenberg, LeMansWinningTeam, Porsche Team]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: LeMansWinningTeam Context triple: [Nico Hülkenberg, LeMansWinningTeam, Porsche Team]
-
A.
LeMansWinStreak
Indicates a continuous sequence of victories achieved by the same participant in Le Mans races.
-
B.
WECDebutYear
Indicates the year in which an entity made its debut or first appearance in World Extreme Cagefighting (WEC).
-
C.
racingTeam
chosen
Indicates that one entity is a racing team associated with, employing, or represented by the other entity in a competitive racing context.
-
D.
firstFormulaOneTeam
Indicates the Formula One team for which an entity (typically a driver) first competed.
-
E.
chassisManufacturerOfWinningCar
Indicates that a manufacturer built the chassis of the car that won a particular race or competition.
- 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_69f077eacd0481908ef0bafd74491cd0 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f65f7d3b5c8190937aaddff2879989 |
completed | May 2, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 9:25 a.m.