Triple
T3897303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British AS-90M Braveheart turret design |
E90400
|
entity |
| Predicate | typeOfGunMount |
P52740
|
FINISHED |
| Object | fully enclosed armored turret |
—
|
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: fully enclosed armored turret | Statement: [British AS-90M Braveheart turret design, typeOfGunMount, fully enclosed armored turret]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfGunMount Context triple: [British AS-90M Braveheart turret design, typeOfGunMount, fully enclosed armored turret]
-
A.
bayonetMount
Indicates that one object is equipped with or designed to accept a bayonet-style mounting connection to another object.
-
B.
gunType
Indicates the specific category or kind of gun associated with an entity.
-
C.
gunCalibre
Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
-
D.
gunStabilisation
Indicates that an entity performs or provides stabilization for a gun, reducing its movement or recoil to improve accuracy.
-
E.
ammunitionType
Indicates the specific kind or category of ammunition associated with or used by an entity.
- 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_69aed95d315881908cbf1bf4a7215fbf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1abe2dc81909c18aeae9b286898 |
completed | March 9, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69aee75b5b808190a348a31b1325d3d0 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef1aada308190821a3dfa6af170b3 |
completed | March 9, 2026, 4:13 p.m. |
Created at: March 9, 2026, 3:21 p.m.