Triple
T8440500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MG4 light machine gun |
E199339
|
entity |
| Predicate | ammunitionFeedSystem |
P83373
|
FINISHED |
| Object | belt-fed |
—
|
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: belt-fed | Statement: [MG4 light machine gun, ammunitionFeedSystem, belt-fed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ammunitionFeedSystem Context triple: [MG4 light machine gun, ammunitionFeedSystem, belt-fed]
-
A.
ammunitionLoading
Indicates the action or process of placing ammunition into a weapon or storage system for use.
-
B.
ammunitionCapacity
Indicates the maximum amount of ammunition that something (typically a weapon or container) is designed to hold at one time.
-
C.
ammunitionType
Indicates the specific kind or category of ammunition associated with or used by an entity.
-
D.
fireControlSystem
Indicates a relationship where a system monitors, directs, and coordinates the detection, targeting, and firing of weapons or other actuators to control the application of force or energy.
-
E.
rocketArmament
Indicates that an entity is equipped with or carries rocket-based weaponry as part of its armament.
- 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_69ca8314cd6c8190a6b8c2a1096e18f3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe30fba4081908bfdef3faf5baceb |
completed | March 31, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69cbd0f5a3648190beb53a139a2d5482 |
completed | March 31, 2026, 1:49 p.m. |
| PDg | Predicate description generation | batch_69cbe30c2d088190b4cb89adb4e88273 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:08 p.m.