Triple
T36045284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citroën Xsara WRC |
E1042654
|
entity |
| Predicate | manufacturersTitlesWithCar |
P185709
|
FINISHED |
| Object | 2003 |
—
|
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: 2003 | Statement: [Citroën Xsara WRC, manufacturersTitlesWithCar, 2003]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: manufacturersTitlesWithCar Context triple: [Citroën Xsara WRC, manufacturersTitlesWithCar, 2003]
-
A.
carManufacturer
Indicates that one entity is the company that produces or manufactures the car represented by the other entity.
-
B.
droveManufacturer
Indicates that a person or agent operated or used a vehicle produced by a specific manufacturer.
-
C.
carModel
Indicates the specific model designation of a car within a particular make or brand.
-
D.
vehicleBrandAssociated
Indicates that there is an association or linkage between a vehicle and a particular brand.
-
E.
fieldedCarBrand
Indicates that a particular car brand has been entered, deployed, or represented (e.g., in a race, event, or lineup) by some agent or organization.
- 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.