Triple
T30605793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Grand Prix |
E779038
|
entity |
| Predicate | fuelUsedInFiction |
P120354
|
FINISHED |
| Object | Allinol |
—
|
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: Allinol | Statement: [World Grand Prix, fuelUsedInFiction, Allinol]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fuelUsedInFiction Context triple: [World Grand Prix, fuelUsedInFiction, Allinol]
-
A.
numberOfUnitsInFiction
Indicates the quantity of discrete units or installments that exist within a fictional work or fictional context.
-
B.
fuelConsumption
Indicates the amount of fuel used by an entity (such as a vehicle or device) over a specified distance, time, or operation.
-
C.
fuelTransport
Indicates the transfer or conveyance of fuel from one location or entity to another.
-
D.
materialUsedInFiction
chosen
Indicates that a particular material (such as a substance or resource) is used, featured, or plays a role within a fictional work or narrative.
-
E.
fuelEffect
Indicates the influence or impact that a given fuel has on a process, system, or outcome.
- 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_69f224a21fc08190abd9d8dd9eb6bb4c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f689b638f88190bc3eb7910a2b19de |
completed | May 2, 2026, 11:33 p.m. |
| PD | Predicate disambiguation | batch_69f67e448a9c8190b591374d98799fe3 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 8:25 p.m.