Triple
T16353155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AS-90 turret |
E397107
|
entity |
| Predicate | mountsGun |
P57777
|
FINISHED |
| Object | 39-calibre 155 mm 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: 39-calibre 155 mm gun | Statement: [AS-90 turret, mountsGun, 39-calibre 155 mm gun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mountsGun Context triple: [AS-90 turret, mountsGun, 39-calibre 155 mm gun]
-
A.
typeOfGunMount
Indicates the specific kind or configuration of gun mounting used to support or attach a gun.
-
B.
weaponMount
chosen
Indicates that one entity serves as a mounting point or support structure for attaching or holding a weapon on another entity.
-
C.
gunType
Indicates the specific category or kind of gun associated with an entity.
-
D.
lightArmament
Indicates that an entity is equipped with or characterized by relatively minimal or lightweight weaponry compared to standard or heavy armament.
-
E.
gunDeckArmament
Indicates the type or configuration of weapons mounted on a ship’s gun deck.
- 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2faccab748190b11e0808e422f2ea |
completed | April 18, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69e226f37ecc819082af58b29b4e39d1 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:07 a.m.