Triple
T33106880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nassau-class battleship |
E847211
|
entity |
| Predicate | antiTorpedoArmament |
P59439
|
FINISHED |
| Object | 8.8 cm guns |
—
|
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: 8.8 cm guns | Statement: [Nassau-class battleship, antiTorpedoArmament, 8.8 cm guns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antiTorpedoArmament Context triple: [Nassau-class battleship, antiTorpedoArmament, 8.8 cm guns]
-
A.
armamentTorpedoes
Indicates that an entity is equipped with torpedoes as part of its armament or weaponry.
-
B.
antiTorpedoProtection
chosen
Indicates a defensive relationship where measures are in place to protect against or mitigate the effects of torpedo attacks.
-
C.
tertiaryArmament
Indicates the relationship where an entity possesses or is equipped with a third-level (tertiary) weapon or armament beyond its primary and secondary armaments.
-
D.
torpedoCaliber
Indicates the specific diameter or size classification of a torpedo used in a given context or system.
-
E.
numberOfTorpedoTubes
Indicates the quantity of torpedo tubes associated with or installed on 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_69f3495686508190b76bf20fa5e00bf7 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d6e7c0248190a5eed4c5bcf83aad |
completed | May 3, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69f6d27224708190b31a541cebe0ff77 |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:26 a.m.