Triple
T35730669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2013 Golden Steering Wheel (compact cars category) |
E1032742
|
entity |
| Predicate | notableWinnerModelYear |
P54787
|
FINISHED |
| Object | 2013 |
—
|
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: 2013 | Statement: [2013 Golden Steering Wheel (compact cars category), notableWinnerModelYear, 2013]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableWinnerModelYear Context triple: [2013 Golden Steering Wheel (compact cars category), notableWinnerModelYear, 2013]
-
A.
winnerModelYear
chosen
Indicates that a model was the winning model for a particular year.
-
B.
notableFirstWinner
Indicates that the subject is the first and notably recognized winner of the object (such as an award, competition, or title).
-
C.
notableWinner
Indicates that the subject is a particularly distinguished or prominent winner of the referenced competition, award, or contest.
-
D.
notableSelectionYear
Indicates the year in which an entity was notably selected for a particular role, honor, list, or recognition.
-
E.
notableProductionYear
Indicates the year in which an entity produced something considered notable or significant.
- 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_69f76e10e59081908d81ad9ce22f40b6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:05 p.m.