Triple
T16352973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sturmgewehr 90 |
E397103
|
entity |
| Predicate | hasMuzzleDevice |
P115810
|
FINISHED |
| Object | flash suppressor |
—
|
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: flash suppressor | Statement: [Sturmgewehr 90, hasMuzzleDevice, flash suppressor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMuzzleDevice Context triple: [Sturmgewehr 90, hasMuzzleDevice, flash suppressor]
-
A.
hasMuzzle
Indicates that one entity possesses or is equipped with a muzzle, typically as a restraining or protective device.
-
B.
muzzleType
chosen
Indicates the specific style or configuration of a muzzle associated with an entity, such as a weapon or animal.
-
C.
hasArrestingGear
Indicates that an entity is equipped with a system or mechanism used to rapidly decelerate and stop another entity, typically during landing or capture.
-
D.
typeOfGunMount
Indicates the specific kind or configuration of gun mounting used to support or attach a gun.
-
E.
hasChamber
Indicates that one entity possesses, contains, or is associated with a distinct enclosed space or compartment (a chamber).
- 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.