Triple
T37590978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingston–Seattle fast ferry |
E935259
|
entity |
| Predicate | passengerVehiclesCarried |
P54685
|
FINISHED |
| Object | no |
—
|
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: no | Statement: [Kingston–Seattle fast ferry, passengerVehiclesCarried, no]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: passengerVehiclesCarried Context triple: [Kingston–Seattle fast ferry, passengerVehiclesCarried, no]
-
A.
numberOfPassengerCars
chosen
Indicates the total count of passenger cars associated with or contained in a given entity or context.
-
B.
vehicleCarrying
Indicates that one vehicle is transporting, holding, or supporting another entity as its load or cargo.
-
C.
passengerCount
Indicates the number of passengers associated with a given entity, such as a vehicle or trip.
-
D.
transportCapacity
Indicates the maximum quantity of people, goods, or materials that can be transported by an entity or system within a given operation or time frame.
-
E.
usesPassengerCars
Indicates that an entity operates or employs passenger cars as part of its activities or services.
- 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_69f76ecf39c081909baffe597bb55273 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbb084760c8190a1554985d3c3cb7a |
completed | May 6, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69fbadf3cb548190ba3b7514f76b790a |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:18 p.m.