Triple
T6301520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Josef Newgarden |
E141265
|
entity |
| Predicate | hasNumberOfIndyCarChampionships |
P51155
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Josef Newgarden, hasNumberOfIndyCarChampionships, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfIndyCarChampionships Context triple: [Josef Newgarden, hasNumberOfIndyCarChampionships, multiple]
-
A.
driversChampionships
chosen
Indicates the number of drivers’ championship titles an entity has won or is associated with.
-
B.
hasChampionships
Indicates that one entity possesses or has won one or more championships associated with another entity.
-
C.
raceWins
Indicates that one participant wins or finishes ahead of another in a race or competitive event.
-
D.
totalPolePositions
Indicates the total number of times an entity has achieved pole position in qualifying or starting order across all relevant events.
-
E.
associatedChampionshipCount
Indicates the number of championships that are linked or related to a given entity.
- 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_69c008cf0ad4819095def81e2bd42f9f |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0645bb41481909294b06e2b3e1845 |
completed | March 22, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69c060e311b48190b1c74a5cf9435623 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:27 p.m.