Triple
T1117905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | K9 Thunder |
E11141
|
entity |
| Predicate | ammunitionCapacity |
P25151
|
FINISHED |
| Object | 48 rounds of 155 mm ammunition |
—
|
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: 48 rounds of 155 mm ammunition | Statement: [K9 Thunder, ammunitionCapacity, 48 rounds of 155 mm ammunition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ammunitionCapacity Context triple: [K9 Thunder, ammunitionCapacity, 48 rounds of 155 mm ammunition]
-
A.
ammunitionType
Indicates the specific kind or category of ammunition associated with or used by an entity.
-
B.
gunCalibre
Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
-
C.
numberOfShotsFired
Indicates the total count of shots that were discharged in the described event or action.
-
D.
weaponCapability
Indicates that one entity has the ability to use, deploy, or function as a weapon against another entity or target.
-
E.
primaryArmament
Indicates the main weapon or principal offensive system that an entity (such as a vehicle, vessel, or platform) is equipped with or uses.
- F. None of above. chosen
Provenance (4 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_69a493252a648190ac48f8742474a5e8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4562f48190831e959f5f309956 |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bc47fce48190825d3a877251f789 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:43 p.m.