Triple
T35330637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terry Labonte |
E1020305
|
entity |
| Predicate | CupSeriesChampionships |
P108047
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Terry Labonte, CupSeriesChampionships, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: CupSeriesChampionships Context triple: [Terry Labonte, CupSeriesChampionships, 2]
-
A.
NASCARCupSeriesChampionships
chosen
Indicates the number of NASCAR Cup Series championship titles an entity has won.
-
B.
NASCARCupSeriesChampionshipSeason
Indicates the relationship in which a NASCAR Cup Series season results in the determination of a series champion.
-
C.
CARTChampionships
Indicates the number of CART (Championship Auto Racing Teams) series championships an entity has won.
-
D.
NASCARCupPoles
Indicates that a subject has achieved one or more pole positions (fastest qualifying times earning the first starting spot) in NASCAR Cup Series races.
-
E.
NASCARChampionships
Indicates the number of NASCAR championships an entity has won or been awarded.
- 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_69f79533b88c8190934ec4cb21770e24 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.