Triple
T13202955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 5.56×45mm NATO |
E314285
|
entity |
| Predicate | hasShoulderDiameter |
P109030
|
FINISHED |
| Object | 9.00 mm |
—
|
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: 9.00 mm | Statement: [5.56×45mm NATO, hasShoulderDiameter, 9.00 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShoulderDiameter Context triple: [5.56×45mm NATO, hasShoulderDiameter, 9.00 mm]
-
A.
hasDiameterClass
Indicates that an entity is associated with a specific category or range based on the size of its diameter.
-
B.
shoulderHeightRange
Indicates the range of vertical height measured from the ground to an entity’s shoulders.
-
C.
hasShoulderButtons
Indicates that an object, typically a device or controller, includes buttons positioned on its shoulders or top side edges.
-
D.
hasShoulderPatchShape
Indicates that one entity possesses a shoulder patch whose form or outline matches the specified shape.
-
E.
shellDiameter
Indicates the diameter measurement of a shell, typically specifying the distance across it at its widest point.
- 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_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc6bc108190b5a6a265bf6e9fd4 |
completed | April 10, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69d98ceeb22c8190a6be666031d9e5a4 |
completed | April 10, 2026, 11:51 p.m. |
Created at: April 9, 2026, 9:16 p.m.