Triple
T17610254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langley Aerodrome |
E428947
|
entity |
| Predicate | unmannedModelsOutcome |
P128268
|
FINISHED |
| Object | achieved short powered flights |
—
|
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: achieved short powered flights | Statement: [Langley Aerodrome, unmannedModelsOutcome, achieved short powered flights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: unmannedModelsOutcome Context triple: [Langley Aerodrome, unmannedModelsOutcome, achieved short powered flights]
-
A.
isUncrewedVariantOf
Indicates that one entity is an uncrewed (unmanned) version or model derived from another, typically crewed, entity.
-
B.
isUncrewed
Indicates that an object, vehicle, or mission operates without any human crew physically on board.
-
C.
spacecraftModel
Indicates that one entity is the specific model or design type of a spacecraft associated with another entity.
-
D.
usModelsSim
Indicates that two models are similar or comparable in the context of U.S.-specific characteristics, standards, or usage.
-
E.
numberOfModels
Indicates the quantity or count of models associated with a given entity or context.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d2d294881908380b2ab0b4d2503 |
completed | April 19, 2026, 5:50 a.m. |
| PD | Predicate disambiguation | batch_69e3cdd7da34819099bc9481c5a79bab |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 5:51 a.m.