Triple
T17109347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OT-34 flamethrower tank |
E415183
|
entity |
| Predicate | mainGun |
P6066
|
FINISHED |
| Object | 76.2 mm 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: 76.2 mm gun | Statement: [OT-34 flamethrower tank, mainGun, 76.2 mm gun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainGun Context triple: [OT-34 flamethrower tank, mainGun, 76.2 mm gun]
-
A.
mainGunModel
Indicates the specific model or type designation of the primary gun or main weapon system used by an entity.
-
B.
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.
-
C.
numberOfMainBatteryGuns
Indicates the quantity of primary (main) battery guns that an entity, typically a warship or similar platform, is equipped with.
-
D.
gun
Indicates that one entity uses, carries, or is associated with a gun in relation to another entity or context.
-
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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc29c884819092a97d9663a1b1f7 |
completed | April 18, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69e35d6b1b988190a8d6b6fe78c35e59 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:35 a.m.