Triple
T5786543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London Buses |
E128280
|
entity |
| Predicate | usesVehicleTechnology |
P65838
|
FINISHED |
| Object | hybrid buses |
—
|
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: hybrid buses | Statement: [London Buses, usesVehicleTechnology, hybrid buses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesVehicleTechnology Context triple: [London Buses, usesVehicleTechnology, hybrid buses]
-
A.
supportsVehicle
Indicates that one entity provides the necessary strength, stability, or structure to bear the weight of a vehicle.
-
B.
motorizedUse
Indicates that an entity is used or operated by means of a motor or engine, rather than by human or animal power.
-
C.
hasNavigationTechnology
Indicates that an entity is equipped with or utilizes a system or technology for determining or guiding its position, route, or movement.
-
D.
vehicleUsed
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
-
E.
laterUsedTechnology
Indicates that one entity adopted or employed a technology after another entity had already used it.
- 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_69c0084450048190bc647b649a05136b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a1c29d48190af36cc855bb491dd |
completed | March 22, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69c021d2cd608190b98a7e3aa7001d27 |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c024861bc88190a17782c1982fbb3e |
completed | March 22, 2026, 5:19 p.m. |
Created at: March 22, 2026, 3:51 p.m.