Triple
T25003234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | flynas |
E625772
|
entity |
| Predicate | aircraftTypeFocus |
P45618
|
FINISHED |
| Object | narrow-body aircraft |
—
|
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: narrow-body aircraft | Statement: [flynas, aircraftTypeFocus, narrow-body aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftTypeFocus Context triple: [flynas, aircraftTypeFocus, narrow-body aircraft]
-
A.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
B.
typeOfAviation
Indicates the specific category or kind of aviation to which an entity belongs (e.g., commercial, military, private).
-
C.
aircraftTypeManaged
Indicates that one entity is responsible for managing or overseeing a particular type or category of aircraft.
-
D.
poweredAircraftType
Indicates that one entity is a type or category of aircraft that is propelled by an onboard power source (e.g., engines), as opposed to being unpowered.
-
E.
typicalAircraftTypeCategory
chosen
Indicates the general class or category of aircraft type that is most commonly associated with or used in a given context.
- 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_69e2ff26c50481908bc82e799c9e6587 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f44b0d1ed48190bcde75a65c8f86a0 |
completed | May 1, 2026, 6:41 a.m. |
| PD | Predicate disambiguation | batch_69f442c0c2e88190acd7f170f10ccef6 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 6:05 a.m.