Triple
T1341959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pennsylvania-class battleship |
E28483
|
entity |
| Predicate | gunTurretConfiguration |
P27374
|
FINISHED |
| Object | four triple 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: four triple turrets | Statement: [Pennsylvania-class battleship, gunTurretConfiguration, four triple turrets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gunTurretConfiguration Context triple: [Pennsylvania-class battleship, gunTurretConfiguration, four triple turrets]
-
A.
turret
Indicates that an entity is equipped with or associated with a turret, typically a rotating weapon or defense mechanism.
-
B.
turretPlacement
Indicates the spatial or positional relationship defining where a turret is placed relative to its environment or reference objects.
-
C.
turretCrew
Indicates that an entity serves as a crew member operating or manning a turret associated with another entity.
-
D.
turretBasedOn
Indicates that one turret is derived from, modeled after, or constructed using the design or components of another turret.
-
E.
gunType
Indicates the specific category or kind of gun 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_69a49854eb3481908c7d56b2e449a290 |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c215fc008190b01fd8150b9f3b2a |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4bef3e8fc8190ac9a1ba9b5879483 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c06721488190ac7f6e012f21af3d |
completed | March 1, 2026, 10:40 p.m. |
Created at: March 1, 2026, 7:56 p.m.