Triple
T11930616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BMP-2 |
E283899
|
entity |
| Predicate | gunElevation |
P102222
|
FINISHED |
| Object | +74 degrees (approximate) |
—
|
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: +74 degrees (approximate) | Statement: [BMP-2, gunElevation, +74 degrees (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gunElevation Context triple: [BMP-2, gunElevation, +74 degrees (approximate)]
-
A.
gunElevationRange
Indicates the range of vertical angles through which a gun can be elevated or depressed relative to a reference plane.
-
B.
gunStabilisation
Indicates that an entity performs or provides stabilization for a gun, reducing its movement or recoil to improve accuracy.
-
C.
gunTurretConfiguration
Indicates the specific arrangement, placement, and setup of gun turrets in a system or structure.
-
D.
weaponMount
Indicates that one entity serves as a mounting point or support structure for attaching or holding a weapon on another entity.
-
E.
typeOfGunMount
Indicates the specific kind or configuration of gun mounting used to support or attach a gun.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90303a9a88190a4044e6310ba9b4b |
completed | April 10, 2026, 2:02 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3af0188190bfb22be5c97b3349 |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8d399d58c81908dab572aa82426d7 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 8, 2026, 9:45 p.m.