Triple
T2685241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS South Dakota (BB-57) |
E57468
|
entity |
| Predicate | armamentAntiAircraft |
P674
|
FINISHED |
| Object | 40 mm Bofors guns |
—
|
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: 40 mm Bofors guns | Statement: [USS South Dakota (BB-57), armamentAntiAircraft, 40 mm Bofors guns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armamentAntiAircraft Context triple: [USS South Dakota (BB-57), armamentAntiAircraft, 40 mm Bofors guns]
-
A.
airDefenseSystemComponent
chosen
Indicates that one entity is a component or subsystem of an air defense system associated with another entity.
-
B.
airDefenseSystem
Indicates a defensive military system designed to detect, track, and engage airborne threats such as aircraft or missiles.
-
C.
opponentAircraft
Indicates that one aircraft is an adversary or opposing aircraft relative to another in a conflict or competitive context.
-
D.
armamentStations
Indicates a relationship where specific locations or mounts on a platform (such as a vehicle, vessel, or structure) are designated for installing or carrying weapons or armaments.
-
E.
artilleryType
Indicates the specific category or kind of artillery associated with an entity or event.
- 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_69ab4a5028388190a36f3baf1588309e |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd9edba5c8190b86d6cba0f1964e2 |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd81c9b4c81908e5e0da6ac5f828b |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.