Triple
T3738490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carl-Gustaf recoilless rifle |
E79642
|
entity |
| Predicate | supportsAmmunitionType |
P6074
|
FINISHED |
| Object | high-explosive anti-tank (HEAT) |
—
|
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: high-explosive anti-tank (HEAT) | Statement: [Carl-Gustaf recoilless rifle, supportsAmmunitionType, high-explosive anti-tank (HEAT)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsAmmunitionType Context triple: [Carl-Gustaf recoilless rifle, supportsAmmunitionType, high-explosive anti-tank (HEAT)]
-
A.
ammunitionType
chosen
Indicates the specific kind or category of ammunition associated with or used by an entity.
-
B.
ammunitionCapacity
Indicates the maximum amount of ammunition that something (typically a weapon or container) is designed to hold at one time.
-
C.
armamentCapacity
Indicates the maximum quantity or type of weapons or munitions that something is designed or allowed to carry.
-
D.
supportsWeapon
Indicates that one entity is capable of accommodating, using, or being compatible with a specified weapon.
-
E.
gunType
Indicates the specific category or kind of gun associated with an 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_69ad8b115610819095b02007da5ca3cb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb3e9248819098d481fe29e1c628 |
completed | March 8, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69adc048f28c819092bed16a95a3cac1 |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:34 p.m.