Triple
T8054162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russian cruiser Admiral Nakhimov |
E187752
|
entity |
| Predicate | gunArmament |
P7135
|
FINISHED |
| Object | AK-130 130 mm dual-purpose gun |
—
|
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: AK-130 130 mm dual-purpose gun | Statement: [Russian cruiser Admiral Nakhimov, gunArmament, AK-130 130 mm dual-purpose gun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gunArmament Context triple: [Russian cruiser Admiral Nakhimov, gunArmament, AK-130 130 mm dual-purpose gun]
-
A.
gunType
Indicates the specific category or kind of gun associated with an entity.
-
B.
armedVariants
Indicates that one entity is a version or model of another that is equipped with weapons or enhanced armaments.
-
C.
gun
chosen
Indicates that one entity uses, carries, or is associated with a gun in relation to another entity or context.
-
D.
gunCalibre
Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
-
E.
weaponsUsed
Indicates that one entity employed or utilized another entity as a weapon in carrying out an action or event.
- 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_69ca82b15e948190a62fd7af5218426a |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3f9fb8dc8190bacc1f66ddfd1cbf |
completed | March 31, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69cb049a1b9c8190811c396421ebf9c9 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:25 p.m.