Triple
T22712306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cannone da 75/27 modello 06 |
E561633
|
entity |
| Predicate | hasGunCaliber |
P6076
|
FINISHED |
| Object | 75 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: 75 mm | Statement: [Cannone da 75/27 modello 06, hasGunCaliber, 75 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGunCaliber Context triple: [Cannone da 75/27 modello 06, hasGunCaliber, 75 mm]
-
A.
gunCalibre
chosen
Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
-
B.
hasSmallCalibreGuns
Indicates that the subject is equipped with or possesses guns of relatively small calibre compared to standard or typical armaments.
-
C.
hasArtilleryCaliber
Indicates that an artillery piece is characterized by or equipped with a specific caliber (diameter) of its gun barrel or ammunition.
-
D.
hasChamberSize
Indicates a relationship where an entity is associated with, or characterized by, a specific size of a chamber or internal compartment.
-
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_69e2454f1348819088d83f420925a5c1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1790998fc8190962e21a28dd08d29 |
completed | April 29, 2026, 3:20 a.m. |
| PD | Predicate disambiguation | batch_69ee62bd657c81909f7b01245b080a5f |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:18 p.m.