Triple
T15683771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Takao class |
E377643
|
entity |
| Predicate | armamentCharacteristic |
P7256
|
FINISHED |
| Object | heavy torpedo armament |
—
|
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: heavy torpedo armament | Statement: [Takao class, armamentCharacteristic, heavy torpedo armament]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armamentCharacteristic Context triple: [Takao class, armamentCharacteristic, heavy torpedo armament]
-
A.
militaryCharacteristic
chosen
Indicates that one entity possesses a specific military-related attribute, quality, or feature in relation to another entity or context.
-
B.
armamentCategory
Indicates the classification of a weapon or military equipment according to its type or role in armament systems.
-
C.
armamentConfiguration
Indicates how weapons or armaments are arranged, equipped, or configured on an entity in a given context.
-
D.
armamentCount
Indicates the number of weapons or armaments associated with an entity.
-
E.
armamentCapacity
Indicates the maximum quantity or type of weapons or munitions that something is designed or allowed to carry.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f31b5b881908e46ecd9fc6048ab |
completed | April 16, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69deda8c856c8190882330114f9a1a5f |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:17 a.m.