Triple
T2416736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Saratoga |
E52321
|
entity |
| Predicate | airGroup |
P37788
|
FINISHED |
| Object | carrier-based 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: carrier-based aircraft | Statement: [USS Saratoga, airGroup, carrier-based aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airGroup Context triple: [USS Saratoga, airGroup, carrier-based aircraft]
-
A.
airGroupType
Indicates the classification or category of an air group based on its role, composition, or operational function.
-
B.
airGroupSize
Indicates the number of units or elements grouped together in an air-related context (such as aircraft in a formation or air assets in an operation).
-
C.
airSupport
Indicates that one entity provides aerial assistance or backing to another, typically through aircraft-based protection, transport, or attack.
-
D.
airWingType
Indicates the classification or category of an air wing associated with an entity.
-
E.
airPower
Indicates the extent to which one entity can project, control, or influence force through the use of aircraft and other aerial capabilities over another entity or area.
- 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_69ab495622948190bc6bc6e4cddaf645 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc94eafd481909eeff689e5bf5960 |
completed | March 7, 2026, 6:44 a.m. |
| PD | Predicate disambiguation | batch_69abc5a6cbd0819086c0716e266b7ebb |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc6011e348190b6f9c038c7559289 |
completed | March 7, 2026, 6:30 a.m. |
Created at: March 6, 2026, 9:42 p.m.