Triple
T34461699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Wyoming (BB-32) |
E884657
|
entity |
| Predicate | armamentModernization |
P179398
|
FINISHED |
| Object | received anti-aircraft guns |
—
|
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: received anti-aircraft guns | Statement: [USS Wyoming (BB-32), armamentModernization, received anti-aircraft guns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armamentModernization Context triple: [USS Wyoming (BB-32), armamentModernization, received anti-aircraft guns]
-
A.
armamentCategory
Indicates the classification of a weapon or military equipment according to its type or role in armament systems.
-
B.
militaryTechnology
Indicates that one entity is a type of military-related technology used for defense, combat, or warfare purposes.
-
C.
plannedArmament
Indicates that an entity has a specific weapon or set of weapons intended or scheduled to be equipped or deployed in the future.
-
D.
armamentStatus
Indicates the current condition or readiness level of an entity’s weapons or military equipment.
-
E.
armamentStabilization
Indicates that an armament system is equipped with mechanisms or technology to maintain its stability and accuracy despite movement or external disturbances.
- 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_69f349c73a94819094dfcf50d00620b8 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f720cc1bfc8190a16118e3af8e9316 |
completed | May 3, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
| PDg | Predicate description generation | batch_69f71fb0172c81908f23e95ff16b0dec |
completed | May 3, 2026, 10:13 a.m. |
Created at: May 1, 2026, 2 a.m.