Triple
T7328421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keio Line bus services |
E168932
|
entity |
| Predicate | usesVehicleFuelType |
P22119
|
FINISHED |
| Object | diesel (majority of fleet) |
—
|
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: diesel (majority of fleet) | Statement: [Keio Line bus services, usesVehicleFuelType, diesel (majority of fleet)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesVehicleFuelType Context triple: [Keio Line bus services, usesVehicleFuelType, diesel (majority of fleet)]
-
A.
fuelRole
Indicates that one entity serves as the fuel or energy source used or consumed by another entity in a process or operation.
-
B.
laterFuelType
Indicates that one fuel type is used or adopted after another fuel type in time.
-
C.
fuelTypeSupported
Indicates that a system, device, or component is capable of operating with or is designed to accept a specified type of fuel.
-
D.
typeOfGasUsed
Indicates the specific kind of gas that is utilized in relation to an entity or process.
-
E.
typicalFuel
chosen
Indicates the kind of fuel that is normally or most commonly used by an entity (such as a device, vehicle, 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_69c68a54cacc81908e3b773441f19566 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0a879b88190bef0fb6cbae411ff |
completed | March 27, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69c6e77230048190b2c29ca6b3a65b8e |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:03 p.m.