Triple
T29015597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unic |
E737297
|
entity |
| Predicate | vehicleUseCase |
P120677
|
FINISHED |
| Object | goods transport |
—
|
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: goods transport | Statement: [Unic, vehicleUseCase, goods transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleUseCase Context triple: [Unic, vehicleUseCase, goods transport]
-
A.
vehicleFunction
chosen
Indicates the functional role or primary purpose that a vehicle is designed or used to perform.
-
B.
vehicleUsed
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
-
C.
vehicleFor
Indicates that one entity serves as the means of transportation or conveyance for another entity.
-
D.
applicationVehicle
Indicates a relationship where a particular vehicle is used, specified, or associated within the context of an application or application process.
-
E.
vehicleBase
Indicates that one entity serves as the foundational or underlying base for a vehicle-related entity or system.
- 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_69f077ee19f881909af48f9cab00a2e5 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f6617ba4a88190bfc5c305acb4f93f |
completed | May 2, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f660f082508190a95a7888ad66cb2e |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 9:45 a.m.