Triple
T22712337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cannone da 75/27 modello 06 |
E561633
|
entity |
| Predicate | hasGunType |
P6073
|
FINISHED |
| Object | breech-loading gun |
—
|
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: breech-loading gun | Statement: [Cannone da 75/27 modello 06, hasGunType, breech-loading gun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGunType Context triple: [Cannone da 75/27 modello 06, hasGunType, breech-loading gun]
-
A.
hasWeaponType
Indicates that an entity is associated with or equipped with a specific type or category of weapon.
-
B.
gunType
chosen
Indicates the specific category or kind of gun associated with an entity.
-
C.
hasMagazineType
Indicates that an entity is associated with, or classified by, a specific type or category of magazine.
-
D.
gunCalibre
Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
-
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_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.