Triple
T23821729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arleigh Burke-class destroyer |
E589254
|
entity |
| Predicate | hasTorpedoLauncher |
P13762
|
FINISHED |
| Object | Mark 32 triple torpedo tubes |
—
|
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: Mark 32 triple torpedo tubes | Statement: [Arleigh Burke-class destroyer, hasTorpedoLauncher, Mark 32 triple torpedo tubes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTorpedoLauncher Context triple: [Arleigh Burke-class destroyer, hasTorpedoLauncher, Mark 32 triple torpedo tubes]
-
A.
numberOfTorpedoTubes
Indicates the quantity of torpedo tubes associated with or installed on an entity.
-
B.
torpedoCaliber
Indicates the specific diameter or size classification of a torpedo used in a given context or system.
-
C.
numberOfMissileTubes
Indicates the quantity of missile tubes that an entity possesses or is equipped with.
-
D.
armamentTorpedoes
chosen
Indicates that an entity is equipped with torpedoes as part of its armament or weaponry.
-
E.
missileTubesPerBoat
Indicates the number of missile tubes associated with each individual boat in the relationship.
- 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_69e25d18619081909c7fb89d8926f14a |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c7af4d4481908095348fae9e54f4 |
completed | April 29, 2026, 8:56 a.m. |
| PD | Predicate disambiguation | batch_69f156036ad48190bc2ffdaf39218bcb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:59 p.m.