Triple
T213369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Egyptian Armed Forces |
E4763
|
entity |
| Predicate | standardRifle |
P7745
|
FINISHED |
| Object | AK-pattern assault rifles |
—
|
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: AK-pattern assault rifles | Statement: [Egyptian Armed Forces, standardRifle, AK-pattern assault rifles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardRifle Context triple: [Egyptian Armed Forces, standardRifle, AK-pattern assault rifles]
-
A.
typicalWeapon
chosen
Indicates that the object is a weapon commonly or characteristically used by the subject.
-
B.
primaryArmament
Indicates the main weapon or principal offensive system that an entity (such as a vehicle, vessel, or platform) is equipped with or uses.
-
C.
gun
Indicates that one entity uses, carries, or is associated with a gun in relation to another entity or context.
-
D.
gunType
Indicates the specific category or kind of gun associated with an entity.
-
E.
gunCalibre
Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
- 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c313d108190a65d3e939f961bef |
completed | Feb. 28, 2026, 3:08 a.m. |
| PD | Predicate disambiguation | batch_69a25b509400819093a6c1a1bac861e3 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.