Triple
T4859770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tosa-class battleship |
E108627
|
entity |
| Predicate | antiTorpedoProtection |
P59439
|
FINISHED |
| Object | torpedo defense system in hull design |
—
|
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: torpedo defense system in hull design | Statement: [Tosa-class battleship, antiTorpedoProtection, torpedo defense system in hull design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antiTorpedoProtection Context triple: [Tosa-class battleship, antiTorpedoProtection, torpedo defense system in hull design]
-
A.
antiSubmarineArmament
Indicates the type or presence of weapons or equipment specifically designed for anti-submarine warfare associated with an entity.
-
B.
armamentTorpedoes
Indicates that an entity is equipped with torpedoes as part of its armament or weaponry.
-
C.
numberOfTorpedoesHit
Indicates the number of torpedoes that successfully struck a specified target.
-
D.
airDefenseSystem
Indicates a defensive military system designed to detect, track, and engage airborne threats such as aircraft or missiles.
-
E.
torpedoed
Indicates that one entity attacked and struck another entity using a torpedo, typically causing damage or destruction.
- F. None of above. chosen
Provenance (4 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_69bd440b965081908b0557721cae6338 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d5c92148190a314707bdd3ff30f |
completed | March 20, 2026, 3:53 p.m. |
| PD | Predicate disambiguation | batch_69bd6c27334481909ba8ac80854f7d8e |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6cfa8bd881908e376ab286759cc2 |
completed | March 20, 2026, 3:51 p.m. |
Created at: March 20, 2026, 1:26 p.m.