Triple
T2332040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Airlines Flight 93 |
E44223
|
entity |
| Predicate | aircraftEngineType |
P38991
|
FINISHED |
| Object | twin-engine turbofan |
—
|
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: twin-engine turbofan | Statement: [United Airlines Flight 93, aircraftEngineType, twin-engine turbofan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftEngineType Context triple: [United Airlines Flight 93, aircraftEngineType, twin-engine turbofan]
-
A.
aircraftEngineTypeProduced
Indicates that a particular type of aircraft engine is manufactured or produced by a specified entity.
-
B.
wingMountedEngines
Indicates that the engines of an aircraft are mounted on its wings rather than on other parts of the airframe.
-
C.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
D.
numberOfEngines
Indicates the quantity of engines associated with or used by an entity.
-
E.
propellerType
Indicates the specific kind or classification of propeller associated with an entity.
- 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_69a889132b488190bbb43ad4780ddd92 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abcc30c5e881908c5d526d7e7491d0 |
completed | March 7, 2026, 6:56 a.m. |
| PD | Predicate disambiguation | batch_69abc5926d048190a535e3f23d41de2a |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abcc2fa25c8190858c1c541b914f4c |
completed | March 7, 2026, 6:56 a.m. |
Created at: March 4, 2026, 7:51 p.m.