Triple
T15683765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Takao class |
E377643
|
entity |
| Predicate | designedTorpedoMounts |
P63127
|
FINISHED |
| Object | quadruple torpedo tube mounts |
—
|
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: quadruple torpedo tube mounts | Statement: [Takao class, designedTorpedoMounts, quadruple torpedo tube mounts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designedTorpedoMounts Context triple: [Takao class, designedTorpedoMounts, quadruple torpedo tube mounts]
-
A.
armamentTorpedoes
Indicates that an entity is equipped with torpedoes as part of its armament or weaponry.
-
B.
numberOfTorpedoTubes
chosen
Indicates the quantity of torpedo tubes associated with or installed on an entity.
-
C.
numberOfMissileTubes
Indicates the quantity of missile tubes that an entity possesses or is equipped with.
-
D.
missileTubesPerBoat
Indicates the number of missile tubes associated with each individual boat in the relationship.
-
E.
torpedoCaliber
Indicates the specific diameter or size classification of a torpedo used in a given context or system.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f31b5b881908e46ecd9fc6048ab |
completed | April 16, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69deda8c856c8190882330114f9a1a5f |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:17 a.m.