Triple
T9944046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PB4Y-2 Privateer |
E194155
|
entity |
| Predicate | turretConfiguration |
P27374
|
FINISHED |
| Object | multiple powered gun turrets |
—
|
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: multiple powered gun turrets | Statement: [PB4Y-2 Privateer, turretConfiguration, multiple powered gun turrets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turretConfiguration Context triple: [PB4Y-2 Privateer, turretConfiguration, multiple powered gun turrets]
-
A.
gunTurretConfiguration
chosen
Indicates the specific arrangement, placement, and setup of gun turrets in a system or structure.
-
B.
turret
Indicates that an entity is equipped with or associated with a turret, typically a rotating weapon or defense mechanism.
-
C.
turretPlacement
Indicates the spatial or positional relationship defining where a turret is placed relative to its environment or reference objects.
-
D.
turretBasedOn
Indicates that one turret is derived from, modeled after, or constructed using the design or components of another turret.
-
E.
turretCount
Indicates the number of turrets associated with or mounted on a given entity.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb613fbb48190b82a06987310cc96 |
completed | April 2, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9428cc81909b4b4938566d78a7 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:45 p.m.