Triple
T11956501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Williams Grand Prix Engineering |
E284565
|
entity |
| Predicate | driversChampionshipWin |
P102464
|
FINISHED |
| Object | 1980 |
—
|
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: 1980 | Statement: [Williams Grand Prix Engineering, driversChampionshipWin, 1980]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: driversChampionshipWin Context triple: [Williams Grand Prix Engineering, driversChampionshipWin, 1980]
-
A.
driversChampionships
Indicates the number of drivers’ championship titles an entity has won or is associated with.
-
B.
driversTitleWinner
Indicates that the subject is the driver who won the drivers’ championship title in the referenced competition or season.
-
C.
raceWins
Indicates that one participant wins or finishes ahead of another in a race or competitive event.
-
D.
grandPrixRaceWins
Indicates the number of Grand Prix races that an entity has won.
-
E.
championshipWinningCar
Indicates that a car is the specific vehicle that won a particular championship.
- F. None of above. chosen
Provenance (4 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90366fda8819083168c93abad27d4 |
completed | April 10, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3e48e08190b2fee43af4f57323 |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8dd0ba0f88190b7d5e358c27ca184 |
completed | April 10, 2026, 11:20 a.m. |
Created at: April 8, 2026, 9:45 p.m.