Triple
T37791156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BGAD |
E942089
|
entity |
| Predicate | hasTypeOfMunitions |
P6074
|
FINISHED |
| Object | conventional ammunition |
—
|
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: conventional ammunition | Statement: [BGAD, hasTypeOfMunitions, conventional ammunition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfMunitions Context triple: [BGAD, hasTypeOfMunitions, conventional ammunition]
-
A.
ammunitionType
chosen
Indicates the specific kind or category of ammunition associated with or used by an entity.
-
B.
hasWeaponType
Indicates that an entity is associated with or equipped with a specific type or category of weapon.
-
C.
hasMilitaryType
Indicates that an entity is associated with or classified under a specific military category, role, or type.
-
D.
missileTypeCarried
Indicates the specific type or category of missile that is carried by a given platform, launcher, or delivery system.
-
E.
weaponTypeTested
Indicates that a specific type of weapon has been subjected to a test or evaluation in the described context.
- 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_69f76ee5cb0c81909a363d1c929156c0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fff9b126b4819085a4cf8791d388d1 |
completed | May 10, 2026, 3:21 a.m. |
| PD | Predicate disambiguation | batch_69fff8f913a881908d3b7e490d92631f |
completed | May 10, 2026, 3:18 a.m. |
Created at: May 3, 2026, 4:19 p.m.