Triple
T2497322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panther tank |
E52181
|
entity |
| Predicate | hasMainArmament |
P6066
|
FINISHED |
| Object | 7.5 cm KwK 42 L/70 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: 7.5 cm KwK 42 L/70 gun | Statement: [Panther tank, hasMainArmament, 7.5 cm KwK 42 L/70 gun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainArmament Context triple: [Panther tank, hasMainArmament, 7.5 cm KwK 42 L/70 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.
secondaryArmament
Indicates that one entity serves as a secondary or auxiliary weapon system associated with another primary platform or armament.
-
C.
weaponCapability
Indicates that one entity has the ability to use, deploy, or function as a weapon against another entity or target.
-
D.
combatArm
Indicates that one entity serves as a primary fighting or operational warfare branch or component of another entity (such as an organization or military force).
-
E.
hasTurrets
Indicates that an entity is equipped with or possesses one or more turrets.
- 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_69ab4955111c8190835bf619adec21ff |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1ad2f8c81908853e97d75081e84 |
completed | March 7, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69abd0b980b481908d4932bcea4a6167 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.