Triple
T9603210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Washington (BB-47) |
E231901
|
entity |
| Predicate | armorConningTower |
P81848
|
FINISHED |
| Object | up to 16 inches |
—
|
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: up to 16 inches | Statement: [USS Washington (BB-47), armorConningTower, up to 16 inches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armorConningTower Context triple: [USS Washington (BB-47), armorConningTower, up to 16 inches]
-
A.
armourConningTowerThickness
chosen
Indicates the thickness of the armor protecting a vessel’s conning tower.
-
B.
turret
Indicates that an entity is equipped with or associated with a turret, typically a rotating weapon or defense mechanism.
-
C.
antiTorpedoProtection
Indicates a defensive relationship where measures are in place to protect against or mitigate the effects of torpedo attacks.
-
D.
hasTurrets
Indicates that an entity is equipped with or possesses one or more turrets.
-
E.
hasTower
Indicates that one entity possesses, contains, or is characterized by the presence of a tower.
- 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_69ca8484838c8190b2049199d22fef70 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a5af8f0819089408ed630afa812 |
completed | April 1, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69ccd5a6fd2481908efd131e207b8143 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:08 p.m.