Triple
T16285759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | K21 infantry fighting vehicle |
E395383
|
entity |
| Predicate | armamentStabilization |
P122528
|
FINISHED |
| Object | stabilized main 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: stabilized main gun | Statement: [K21 infantry fighting vehicle, armamentStabilization, stabilized main gun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armamentStabilization Context triple: [K21 infantry fighting vehicle, armamentStabilization, stabilized main gun]
-
A.
armamentStatus
Indicates the current condition or readiness level of an entity’s weapons or military equipment.
-
B.
armamentCategory
Indicates the classification of a weapon or military equipment according to its type or role in armament systems.
-
C.
armsTrade
Indicates the buying, selling, or exchange of weapons or military equipment between parties.
-
D.
armamentConfiguration
Indicates how weapons or armaments are arranged, equipped, or configured on an entity in a given context.
-
E.
armamentCount
Indicates the number of weapons or armaments associated with an entity.
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24914bda08190a5d6315414ee3f76 |
completed | April 17, 2026, 2:52 p.m. |
| PD | Predicate disambiguation | batch_69e219f68d308190b71c1601303f0628 |
completed | April 17, 2026, 11:31 a.m. |
| PDg | Predicate description generation | batch_69e21e56e0348190a3d9475360231a70 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:05 a.m.