Triple
T35987554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2004 World Rally Championship |
E1040753
|
entity |
| Predicate | constructorsChampionCar |
P72467
|
FINISHED |
| Object | Citroën Xsara WRC |
—
|
NE NERFINISHED |
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: Citroën Xsara WRC | Statement: [2004 World Rally Championship, constructorsChampionCar, Citroën Xsara WRC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: constructorsChampionCar Context triple: [2004 World Rally Championship, constructorsChampionCar, Citroën Xsara WRC]
-
A.
championCarMake
Indicates that a particular car make is the champion or winning make in a given context, such as a race, season, or competition.
-
B.
championshipWinningCar
chosen
Indicates that a car is the specific vehicle that won a particular championship.
-
C.
hasCarConstructor
Indicates that an entity is associated with a specific car constructor (manufacturer or builder) responsible for producing its car.
-
D.
constructorsChampionships
Indicates the number of championship titles won by a constructor (e.g., a racing team) in a given competition or series.
-
E.
carManufacturer
Indicates that one entity is the company that produces or manufactures the car represented by the other entity.
- 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_69f76e28293c8190ae3f4e2208b87117 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fda5003cdc8190a558501271389912 |
completed | May 8, 2026, 8:55 a.m. |
| PD | Predicate disambiguation | batch_69fda05bfc2c819096821a5300e9bb24 |
completed | May 8, 2026, 8:35 a.m. |
Created at: May 3, 2026, 4:07 p.m.