Triple
T1778465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pizarro infantry fighting vehicle |
E39233
|
entity |
| Predicate | gunElevationRange |
P32309
|
FINISHED |
| Object | approximately -10 to +45 degrees |
—
|
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: approximately -10 to +45 degrees | Statement: [Pizarro infantry fighting vehicle, gunElevationRange, approximately -10 to +45 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gunElevationRange Context triple: [Pizarro infantry fighting vehicle, gunElevationRange, approximately -10 to +45 degrees]
-
A.
gunCalibre
Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
-
B.
ammunitionCapacity
Indicates the maximum amount of ammunition that something (typically a weapon or container) is designed to hold at one time.
-
C.
gunStabilisation
Indicates that an entity performs or provides stabilization for a gun, reducing its movement or recoil to improve accuracy.
-
D.
gunType
Indicates the specific category or kind of gun associated with an entity.
-
E.
rateOfFire
Indicates the frequency at which a weapon or system can discharge projectiles or shots over a given period of time.
- 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab74dc9d1481908084ef07872a71f8 |
completed | March 7, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69aa61cf3ca881908641fd73ce2f7c9d |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab74db3dbc8190ab256a4e158062b8 |
completed | March 7, 2026, 12:44 a.m. |
Created at: March 4, 2026, 7:31 p.m.