Triple
T45536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Marine Corps |
E892
|
entity |
| Predicate | primaryAircraftRole |
P2860
|
FINISHED |
| Object | close air support |
—
|
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: close air support | Statement: [United States Marine Corps, primaryAircraftRole, close air support]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryAircraftRole Context triple: [United States Marine Corps, primaryAircraftRole, close air support]
-
A.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
B.
primaryGermanFighterAircraft
Indicates that the subject is the main or principal fighter aircraft used by Germany in a given context or time period.
-
C.
aircraftFlown
Indicates that an entity (typically a person or organization) operates or pilots a particular aircraft.
-
D.
primaryBritishFighterAircraft
Indicates that an aircraft serves as the main or most important fighter aircraft used by British military forces.
-
E.
aircraftManufacturerUsed
Indicates that a particular aircraft manufacturer was employed or utilized in relation to another entity, such as for production, design, or supply purposes.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24ba7016481909d595402712db6e2 |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24abbd32c81908cec461d9097662e |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24ba5da048190a484963cb5a9bb2b |
completed | Feb. 28, 2026, 1:57 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.