Triple
T19441568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pacific Wheel |
E486361
|
entity |
| Predicate | totalPassengerCapacity |
P11680
|
FINISHED |
| Object | up to 120 passengers |
—
|
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: up to 120 passengers | Statement: [Pacific Wheel, totalPassengerCapacity, up to 120 passengers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalPassengerCapacity Context triple: [Pacific Wheel, totalPassengerCapacity, up to 120 passengers]
-
A.
maximumPassengerCapacity
chosen
Indicates the greatest number of passengers that an entity is designed or allowed to carry at one time.
-
B.
passengerCapacityCategory
Indicates the classification of an entity based on the number of passengers it is designed or allowed to carry.
-
C.
designedCargoCapacity
Indicates the maximum amount of cargo an object (such as a vehicle or container) was originally engineered or specified to carry.
-
D.
crewAndPassengersCount
Indicates the total number of people on a vehicle or vessel, combining both crew members and passengers.
-
E.
hasPassengerArea
Indicates that an object or vehicle includes a designated area intended for carrying passengers.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63365343081908683c29f6c4c194b |
completed | April 20, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69e4fd6e806081909053f325ba01ab6b |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:38 p.m.