Triple
T7603423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RS-25D |
E180039
|
entity |
| Predicate | numberPerVehicle |
P24242
|
FINISHED |
| Object | three on each Space Shuttle orbiter |
—
|
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: three on each Space Shuttle orbiter | Statement: [RS-25D, numberPerVehicle, three on each Space Shuttle orbiter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberPerVehicle Context triple: [RS-25D, numberPerVehicle, three on each Space Shuttle orbiter]
-
A.
numberOfVehicles
Indicates the total count of vehicles associated with a given entity or context.
-
B.
numberOfRidersPerVehicle
chosen
Indicates the quantity of riders associated with each individual vehicle in the relationship.
-
C.
numberOfCarsPerUnit
Indicates the quantity of cars associated with each single unit of a specified measure (such as time, distance, or entity).
-
D.
numberOfPassengerCars
Indicates the total count of passenger cars associated with or contained in a given entity or context.
-
E.
rowsPerCar
Indicates the number of rows associated with or allocated to each individual car.
- 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_69c69f3567008190ab01d2ca7b53584a |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f9fa633081909660f653f5b073cd |
completed | March 27, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e485f88190910b39da52a955fe |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:54 p.m.