Triple
T17990122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rooikat armoured fighting vehicle |
E430344
|
entity |
| Predicate | mainGunCalibre |
P6076
|
FINISHED |
| Object | 76 mm |
—
|
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 mm | Statement: [Rooikat armoured fighting vehicle, mainGunCalibre, 76 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainGunCalibre Context triple: [Rooikat armoured fighting vehicle, mainGunCalibre, 76 mm]
-
A.
gunCalibre
chosen
Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
-
B.
mainGunModel
Indicates the specific model or type designation of the primary gun or main weapon system used by an entity.
-
C.
primaryArmament
Indicates the main weapon or principal offensive system that an entity (such as a vehicle, vessel, or platform) is equipped with or uses.
-
D.
lightArmament
Indicates that an entity is equipped with or characterized by relatively minimal or lightweight weaponry compared to standard or heavy armament.
-
E.
ammunitionCapacity
Indicates the maximum amount of ammunition that something (typically a weapon or container) is designed to hold at one time.
- 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b29f127c81908b0c4cb3787e002c |
completed | April 19, 2026, 10:46 a.m. |
| PD | Predicate disambiguation | batch_69e3f90039e4819080527f860dca042e |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:23 a.m.