Triple
T36123624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citroën C4 WRC |
E1044814
|
entity |
| Predicate | worldTitlesConstructorsCount |
P197784
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Citroën C4 WRC, worldTitlesConstructorsCount, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldTitlesConstructorsCount Context triple: [Citroën C4 WRC, worldTitlesConstructorsCount, 3]
-
A.
worldRallyChampionshipTitles
Indicates the number of World Rally Championship titles an entity has won.
-
B.
championCarMake
Indicates that a particular car make is the champion or winning make in a given context, such as a race, season, or competition.
-
C.
worldDriversChampionCarNumber
Indicates the car number driven by the Formula 1 World Drivers' Champion in a given season.
-
D.
championshipWinningCar
Indicates that a car is the specific vehicle that won a particular championship.
-
E.
driversChampionships
Indicates the number of drivers’ championship titles an entity has won or is associated with.
- 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_69f76e356c908190abc6ca1e6a05b011 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69feaa483fcc81909d8a46b38a8717bf |
completed | May 9, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69fea8c9d45c81908ccc8619e5fefac1 |
completed | May 9, 2026, 3:23 a.m. |
| PDg | Predicate description generation | batch_69feaa477f7c81909382b3aa77e7e11c |
completed | May 9, 2026, 3:30 a.m. |
Created at: May 3, 2026, 4:08 p.m.