Triple
T35330503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2000 NASCAR Cup Series |
E1020302
|
entity |
| Predicate | notableChampionCarNumber |
P146457
|
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: [2000 NASCAR Cup Series, notableChampionCarNumber, 18]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableChampionCarNumber Context triple: [2000 NASCAR Cup Series, notableChampionCarNumber, 18]
-
A.
championshipCarNumber
chosen
Indicates the specific car number associated with a championship-winning entry in a racing competition.
-
B.
championshipWinningCar
Indicates that a car is the specific vehicle that won a particular championship.
-
C.
championCarMake
Indicates that a particular car make is the champion or winning make in a given context, such as a race, season, or competition.
-
D.
vehicleNumberInRace
Indicates the specific position or identification number assigned to a vehicle within a particular race.
-
E.
notableVehicleNumber
Indicates that a specific vehicle is identified as notable or significant by a particular number or identifier.
- 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_69f76deacf4481908e7735a5a7715b0a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0324d08190ac5b610cc0f6a38c |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:03 p.m.