Triple
T34708996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York-class battleship |
E1000585
|
entity |
| Predicate | gunTurretArrangement |
P27374
|
FINISHED |
| Object | five twin 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: five twin turrets | Statement: [New York-class battleship, gunTurretArrangement, five twin turrets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gunTurretArrangement Context triple: [New York-class battleship, gunTurretArrangement, five twin turrets]
-
A.
gunTurretConfiguration
chosen
Indicates the specific arrangement, placement, and setup of gun turrets in a system or structure.
-
B.
turretDesign
Indicates a relationship where one entity specifies or defines the design or configuration of a turret associated with another entity.
-
C.
turretPlacement
Indicates the spatial or positional relationship defining where a turret is placed relative to its environment or reference objects.
-
D.
turret
Indicates that an entity is equipped with or associated with a turret, typically a rotating weapon or defense mechanism.
-
E.
primaryArmamentLayout
Indicates how the main weapons or primary armament of an entity are arranged or distributed relative to that 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_69f76dab937881909c86f1b9ad50445f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ffa6b68819090257fed3802c239 |
completed | May 3, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69f7795978c481909e152cd1bd02dd07 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.