Triple
T11363560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nagato class |
E269145
|
entity |
| Predicate | gunArrangement |
P27374
|
FINISHED |
| Object | two superfiring turrets forward and two aft |
—
|
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: two superfiring turrets forward and two aft | Statement: [Nagato class, gunArrangement, two superfiring turrets forward and two aft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gunArrangement Context triple: [Nagato class, gunArrangement, two superfiring turrets forward and two aft]
-
A.
needleArrangement
Indicates how needles are positioned or organized relative to each other in a given context.
-
B.
gunType
Indicates the specific category or kind of gun associated with an entity.
-
C.
arrangement
Indicates a relationship where entities are organized, ordered, or positioned in a particular configuration or sequence relative to one another.
-
D.
cylinderArrangement
Indicates how multiple cylinders are positioned or organized relative to one another.
-
E.
gunTurretConfiguration
chosen
Indicates the specific arrangement, placement, and setup of gun turrets in a system or structure.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d800160a1c81909d115bf89fe54a49 |
completed | April 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69d7e7022d508190996f9be0847c2b41 |
completed | April 9, 2026, 5:50 p.m. |
Created at: April 8, 2026, 9:33 p.m.