Triple
T199028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford Model T |
E4060
|
entity |
| Predicate | fuelCompatibility |
P1585
|
FINISHED |
| Object | kerosene |
—
|
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: kerosene | Statement: [Ford Model T, fuelCompatibility, kerosene]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fuelCompatibility Context triple: [Ford Model T, fuelCompatibility, kerosene]
-
A.
hasRefuellingCapabilityFor
Indicates that one entity is capable of providing or performing refuelling operations for another entity.
-
B.
fueledBy
chosen
Indicates that one entity provides the energy or power source that enables the operation or functioning of another entity.
-
C.
availableEngineDisplacement
Indicates the range or specific values of engine displacement that are offered or applicable for a given entity.
-
D.
driveType
Indicates the type or configuration of the drive mechanism used to power or propel an entity.
-
E.
enginePower
Indicates the power output produced by an engine, typically quantifying its capability to perform work or generate mechanical energy.
- 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_69a254bca59881909a15e1496f1508c7 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a25bcb2c7c8190b0e031e93651182a |
completed | Feb. 28, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69a25b4886b48190b46fd2244648a098 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:44 a.m.