Triple
T37495887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bremerton–Port Orchard foot ferry |
E931825
|
entity |
| Predicate | vehicleCarrying |
P188688
|
FINISHED |
| Object | no vehicles |
—
|
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 vehicles | Statement: [Bremerton–Port Orchard foot ferry, vehicleCarrying, no vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleCarrying Context triple: [Bremerton–Port Orchard foot ferry, vehicleCarrying, no vehicles]
-
A.
vehicleToLoad
Indicates a relationship where a vehicle is associated with, assigned to, or responsible for transporting a particular load.
-
B.
cargoVehicle
Indicates a relationship where a vehicle is used or designated for transporting cargo or goods.
-
C.
vehicleLoadingMethod
Indicates the method or process by which a vehicle is loaded with goods, passengers, or other cargo.
-
D.
transportUnit
Indicates a relationship where one entity serves as a means or unit for transporting another entity from one place to another.
-
E.
vehicleFor
Indicates that one entity serves as the means of transportation or conveyance for another entity.
- 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_69f76ec457a4819094eeb3aed9baac11 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbacaf54648190811ea33b34907e8e |
completed | May 6, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69fba883f770819091059c6f6c6af9f7 |
completed | May 6, 2026, 8:45 p.m. |
| PDg | Predicate description generation | batch_69fbacaea12c8190a4c99e64335f0e7e |
completed | May 6, 2026, 9:03 p.m. |
Created at: May 3, 2026, 4:17 p.m.