Triple
T35754058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2014 Beijing ePrix |
E1033391
|
entity |
| Predicate | safetyCarModel |
P185265
|
FINISHED |
| Object | BMW i8 |
—
|
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: BMW i8 | Statement: [2014 Beijing ePrix, safetyCarModel, BMW i8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyCarModel Context triple: [2014 Beijing ePrix, safetyCarModel, BMW i8]
-
A.
safetyCarSupplier
Indicates that one entity serves as the provider or manufacturer of safety cars for another entity or event.
-
B.
safetyCarDriver
Indicates that an entity serves as the driver of a safety car, typically responsible for leading and controlling the pace of other vehicles in regulated conditions.
-
C.
safetyCarPossible
Indicates that conditions are such that deploying a safety car is a valid or allowable option.
-
D.
safetyCarUsed
Indicates that a safety car was deployed and used during an event or activity.
-
E.
racingModel
Indicates that one entity is a specific model or version designed or configured for racing in relation to another entity.
- 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_69f76e1262f48190a313318665acc189 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69f7bbf812cc8190a16917c5daaff2df |
completed | May 3, 2026, 9:19 p.m. |
Created at: May 3, 2026, 4:06 p.m.