Triple
T9388860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vickers A1E1 Independent |
E225971
|
entity |
| Predicate | armamentPrimaryType |
P6066
|
FINISHED |
| Object | QF 3-pounder gun |
—
|
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: QF 3-pounder gun | Statement: [Vickers A1E1 Independent, armamentPrimaryType, QF 3-pounder gun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armamentPrimaryType Context triple: [Vickers A1E1 Independent, armamentPrimaryType, QF 3-pounder gun]
-
A.
primaryArmament
chosen
Indicates the main weapon or principal offensive system that an entity (such as a vehicle, vessel, or platform) is equipped with or uses.
-
B.
primaryArms
Indicates that the subject possesses or uses the specified arms or weapons as its main or most important set.
-
C.
armamentCategory
Indicates the classification of a weapon or military equipment according to its type or role in armament systems.
-
D.
typicalWeapon
Indicates that the object is a weapon commonly or characteristically used by the subject.
-
E.
lightArmament
Indicates that an entity is equipped with or characterized by relatively minimal or lightweight weaponry compared to standard or heavy armament.
- 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.