Triple
T6674009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Balao-class submarine |
E151803
|
entity |
| Predicate | standardTorpedoLoad |
P13762
|
FINISHED |
| Object | 24 torpedoes |
—
|
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: 24 torpedoes | Statement: [Balao-class submarine, standardTorpedoLoad, 24 torpedoes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardTorpedoLoad Context triple: [Balao-class submarine, standardTorpedoLoad, 24 torpedoes]
-
A.
armamentTorpedoes
chosen
Indicates that an entity is equipped with torpedoes as part of its armament or weaponry.
-
B.
torpedoCaliber
Indicates the specific diameter or size classification of a torpedo used in a given context or system.
-
C.
numberOfTorpedoTubes
Indicates the quantity of torpedo tubes associated with or installed on an entity.
-
D.
numberOfTorpedoesHit
Indicates the number of torpedoes that successfully struck a specified target.
-
E.
antiTorpedoProtection
Indicates a defensive relationship where measures are in place to protect against or mitigate the effects of torpedo attacks.
- 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_69c687f830bc81909eb8b04dbb8450b1 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c0aa8c5c8190a302b261f11b70cb |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0b6d00819086205b8ce30dd045 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:03 p.m.