Triple
T10746172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony |
E253453
|
entity |
| Predicate | aircraftEngineTypeOfAircraft |
P38991
|
FINISHED |
| Object | liquid-cooled inline engine |
—
|
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: liquid-cooled inline engine | Statement: [Tony, aircraftEngineTypeOfAircraft, liquid-cooled inline engine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftEngineTypeOfAircraft Context triple: [Tony, aircraftEngineTypeOfAircraft, liquid-cooled inline engine]
-
A.
aircraftEngineType
chosen
Indicates the specific type or classification of engine that an aircraft uses.
-
B.
aircraftPowerplantType
Indicates the type or category of powerplant (e.g., engine or propulsion system) used by an aircraft.
-
C.
aircraftEngineTypeProduced
Indicates that a particular type of aircraft engine is manufactured or produced by a specified entity.
-
D.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
E.
aircraftEngineManufacturer
Indicates that one entity is the manufacturer of the aircraft engine used by another entity.
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d711b85d9c8190a66f536e2f22ed04 |
completed | April 9, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69d6f30df9948190ab3cdc33977fac14 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:15 p.m.