Triple
T1038477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transformers: The Ride 3D |
E22416
|
entity |
| Predicate | numberOfRidersPerVehicle |
P24242
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Transformers: The Ride 3D, numberOfRidersPerVehicle, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRidersPerVehicle Context triple: [Transformers: The Ride 3D, numberOfRidersPerVehicle, 12]
-
A.
numberOfVehicles
Indicates the total count of vehicles associated with a given entity or context.
-
B.
numberOfCarsPerUnit
Indicates the quantity of cars associated with each single unit of a specified measure (such as time, distance, or entity).
-
C.
crewCountApproximate
Indicates that the relationship specifies an estimated or approximate number of crew members associated with an entity.
-
D.
numberOfWheels
Indicates the quantity of wheels that an entity possesses or is associated with.
-
E.
passengersCountApproximate
Indicates that the number of passengers involved is given as an approximate or estimated count rather than an exact figure.
- 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_69a493d91478819094cc01fb65564bc1 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b97c64a88190bf1119fdd4940bf3 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b729f8488190b2042bd9c625a833 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b97acbf4819087b92a8b29baef46 |
completed | March 1, 2026, 10:11 p.m. |
Created at: March 1, 2026, 7:41 p.m.