Triple
T2916572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese cruiser Tenryu |
E78620
|
entity |
| Predicate | armamentTorpedo |
P13762
|
FINISHED |
| Object | 6 × 533 mm 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: 6 × 533 mm torpedo tubes | Statement: [Japanese cruiser Tenryu, armamentTorpedo, 6 × 533 mm torpedo tubes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armamentTorpedo Context triple: [Japanese cruiser Tenryu, armamentTorpedo, 6 × 533 mm torpedo tubes]
-
A.
armamentTorpedoes
chosen
Indicates that an entity is equipped with torpedoes as part of its armament or weaponry.
-
B.
numberOfTorpedoesHit
Indicates the number of torpedoes that successfully struck a specified target.
-
C.
antiSubmarineArmament
Indicates the type or presence of weapons or equipment specifically designed for anti-submarine warfare associated with an entity.
-
D.
primaryArmament
Indicates the main weapon or principal offensive system that an entity (such as a vehicle, vessel, or platform) is equipped with or uses.
-
E.
ammunitionType
Indicates the specific kind or category of ammunition associated with or used by an entity.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97fd89d88190bc7db4b39058ae3a |
completed | March 8, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9603ddd88190b8bf91bc7517cc21 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:53 p.m.