Triple
T36045287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citroën Xsara WRC |
E1042654
|
entity |
| Predicate | driversTitlesWithCar |
P185710
|
FINISHED |
| Object | 2004 |
—
|
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: 2004 | Statement: [Citroën Xsara WRC, driversTitlesWithCar, 2004]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: driversTitlesWithCar Context triple: [Citroën Xsara WRC, driversTitlesWithCar, 2004]
-
A.
driversTitleWinner
Indicates that the subject is the driver who won the drivers’ championship title in the referenced competition or season.
-
B.
featuresDrivers
Indicates that something includes or highlights specific drivers as notable components or participants.
-
C.
wonDriversTitleFor
Indicates that one entity secured the drivers’ championship title while competing for, or representing, another entity.
-
D.
wonDriversTitleIn
Indicates that a driver secured the drivers’ championship title in a specified competition or season.
-
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_69f76e2e41f8819091f9fb0536920fec |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7c33d59808190b647989a093f3488 |
completed | May 3, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b6e7a881908deb96bedb2713f4 |
completed | May 3, 2026, 9:44 p.m. |
| PDg | Predicate description generation | batch_69f7c29cf36481908e472d4dcb5573b9 |
completed | May 3, 2026, 9:48 p.m. |
Created at: May 3, 2026, 4:07 p.m.