Triple
T682913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lockheed C-130 Hercules |
E13220
|
entity |
| Predicate | propellerType |
P17498
|
FINISHED |
| Object | four-bladed constant-speed (early variants) |
—
|
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: four-bladed constant-speed (early variants) | Statement: [Lockheed C-130 Hercules, propellerType, four-bladed constant-speed (early variants)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: propellerType Context triple: [Lockheed C-130 Hercules, propellerType, four-bladed constant-speed (early variants)]
-
A.
turbineType
Indicates the specific kind or category of turbine associated with or used by an entity.
-
B.
fuselageType
Indicates the specific structural or design category of an aircraft’s fuselage that an entity belongs to or uses.
-
C.
fairingType
Indicates the specific kind or design category of a fairing used in a structure, vehicle, or assembly.
-
D.
landingGearType
Indicates the specific kind or configuration of landing gear that an object (typically an aircraft or vehicle) uses.
-
E.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
- 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a070d4c08190a510a8f9c1ae8076 |
completed | March 1, 2026, 8:24 p.m. |
| PD | Predicate disambiguation | batch_69a49d1f0ccc819088c1527beabcb718 |
completed | March 1, 2026, 8:10 p.m. |
| PDg | Predicate description generation | batch_69a49df19c9481909cc9bc33ed7f011b |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:36 p.m.