Triple
T37300575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zündapp KS 750 |
E925926
|
entity |
| Predicate | typicalArmamentMount |
P52740
|
FINISHED |
| Object | machine gun on sidecar |
—
|
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: machine gun on sidecar | Statement: [Zündapp KS 750, typicalArmamentMount, machine gun on sidecar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalArmamentMount Context triple: [Zündapp KS 750, typicalArmamentMount, machine gun on sidecar]
-
A.
weaponMount
Indicates that one entity serves as a mounting point or support structure for attaching or holding a weapon on another entity.
-
B.
typeOfGunMount
chosen
Indicates the specific kind or configuration of gun mounting used to support or attach a gun.
-
C.
bayonetMount
Indicates that one object is equipped with or designed to accept a bayonet-style mounting connection to another object.
-
D.
missionEquipment
Indicates that certain equipment is assigned to, used for, or associated with carrying out a specific mission.
-
E.
primaryArmamentLayout
Indicates how the main weapons or primary armament of an entity are arranged or distributed relative to that entity.
- 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_69f76eb1bc508190924e9fa5d8acdeb3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.