Triple
T22059097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ernie Irvan |
E545103
|
entity |
| Predicate | bestCupPointsFinish |
P143162
|
FINISHED |
| Object | 3rd |
—
|
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: 3rd | Statement: [Ernie Irvan, bestCupPointsFinish, 3rd]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestCupPointsFinish Context triple: [Ernie Irvan, bestCupPointsFinish, 3rd]
-
A.
bestCupSeriesPointsPosition
chosen
Indicates the highest (best) overall points-based finishing position an entity has achieved in a Cup series standings or championship.
-
B.
bestCupSeasonPointsYear
Indicates the year in which an entity achieved its highest total of Cup season points.
-
C.
bestLeagueFinish
Indicates the highest final position or ranking an entity has ever achieved in a particular league or competition.
-
D.
bestConstructorsChampionshipPosition
Indicates the highest (best) finishing position a constructor has achieved in a constructors’ championship standings.
-
E.
runnersUpPoints
Indicates the number of points awarded to an entity for finishing as a runner-up in a competition or ranking.
- 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_69e11e3377c48190890c17407b9527d6 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1285ac9608190ab4f89d4ee7350d0 |
completed | April 28, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69e6f643ca74819083e8ab78e843f243 |
completed | April 21, 2026, 4 a.m. |
Created at: April 16, 2026, 8:27 p.m.