Triple
T11956546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Subaru World Rally Team |
E284566
|
entity |
| Predicate | worldChampionshipTitlesManufacturers |
P52094
|
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: [Subaru World Rally Team, worldChampionshipTitlesManufacturers, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldChampionshipTitlesManufacturers Context triple: [Subaru World Rally Team, worldChampionshipTitlesManufacturers, 3]
-
A.
worldChampionshipTitles
Indicates the number of world championship titles an entity has won.
-
B.
driversChampionships
Indicates the number of drivers’ championship titles an entity has won or is associated with.
-
C.
championshipWinningCar
Indicates that a car is the specific vehicle that won a particular championship.
-
D.
manufacturerChampionshipsWonInWRC
chosen
Indicates the number of World Rally Championship (WRC) titles a manufacturer has won.
-
E.
worldTitles
Indicates that an entity has won one or more world championship titles in a given field or competition.
- 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_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. |
Created at: April 8, 2026, 9:45 p.m.