Triple
T9388861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vickers A1E1 Independent |
E225971
|
entity |
| Predicate | armamentSecondaryType |
P6067
|
FINISHED |
| Object | machine 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: machine guns | Statement: [Vickers A1E1 Independent, armamentSecondaryType, machine guns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armamentSecondaryType Context triple: [Vickers A1E1 Independent, armamentSecondaryType, machine guns]
-
A.
secondaryArmament
chosen
Indicates that one entity serves as a secondary or auxiliary weapon system associated with another primary platform or armament.
-
B.
primaryArmament
Indicates the main weapon or principal offensive system that an entity (such as a vehicle, vessel, or platform) is equipped with or uses.
-
C.
lightArmament
Indicates that an entity is equipped with or characterized by relatively minimal or lightweight weaponry compared to standard or heavy armament.
-
D.
ammunitionType
Indicates the specific kind or category of ammunition associated with or used by an entity.
-
E.
weaponCategory
Indicates the classification or type of weapon to which an item or armament belongs.
- 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_69ca842e9dcc8190a264119e683cfe04 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd50d6e5f081908102909cb4cbb649 |
completed | April 1, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_69cca53bd6ec81909bf403ce304e5c08 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:45 p.m.