Triple
T15818399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isle Royale Queen IV |
E383536
|
entity |
| Predicate | vehicleTransport |
P99081
|
FINISHED |
| Object | no vehicles carried |
—
|
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 carried | Statement: [Isle Royale Queen IV, vehicleTransport, no vehicles carried]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleTransport Context triple: [Isle Royale Queen IV, vehicleTransport, no vehicles carried]
-
A.
cargoVehicle
Indicates a relationship where a vehicle is used or designated for transporting cargo or goods.
-
B.
transportUnit
chosen
Indicates a relationship where one entity serves as a means or unit for transporting another entity from one place to another.
-
C.
hostVehicle
Indicates that one entity serves as the primary or reference vehicle in relation to another entity or context.
-
D.
cargoSpace
Indicates that one entity provides storage capacity or room for carrying goods, equipment, or other items for another entity.
-
E.
vehicleType
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
- 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_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0c4a552008190863343c9d41ebf3f |
completed | April 16, 2026, 11:14 a.m. |
| PD | Predicate disambiguation | batch_69e0053b847c8190945726c3ddac21cc |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:49 a.m.