Triple
T5365649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 7.62 mm L37A1 machine gun |
E103122
|
entity |
| Predicate | standardNATOCaliber |
P6076
|
FINISHED |
| Object | 7.62×51mm NATO |
—
|
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: 7.62×51mm NATO | Statement: [7.62 mm L37A1 machine gun, standardNATOCaliber, 7.62×51mm NATO]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardNATOCaliber Context triple: [7.62 mm L37A1 machine gun, standardNATOCaliber, 7.62×51mm NATO]
-
A.
standardUSNATOCaliber
Indicates that an item’s caliber conforms to the standard ammunition dimensions used by U.S. and NATO military forces.
-
B.
natoCaliberClass
Indicates that two ammunition types share the same standardized NATO caliber classification.
-
C.
gunCalibre
chosen
Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
-
D.
successorCaliber
Indicates that one entity serves as the successor or follow-up version in terms of quality, standard, or specification relative to another.
-
E.
standardNumber
Indicates that an entity is associated with a canonical or officially recognized reference number used for identification or classification.
- 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_69bd43daa3e4819090b59d127db70e57 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd865eb23481908d32fae4efd86efa |
completed | March 20, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69bd845f41f88190b75b8b64b9e41862 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:02 p.m.