Triple
T23724504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Model 1892 Springfield |
E586231
|
entity |
| Predicate | firearmClass |
P16410
|
FINISHED |
| Object | shoulder-fired weapon |
—
|
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: shoulder-fired weapon | Statement: [U.S. Model 1892 Springfield, firearmClass, shoulder-fired weapon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firearmClass Context triple: [U.S. Model 1892 Springfield, firearmClass, shoulder-fired weapon]
-
A.
gunType
Indicates the specific category or kind of gun associated with an entity.
-
B.
firearmActionType
Indicates the specific type or category of action performed with or by a firearm (such as firing, loading, carrying, or modifying).
-
C.
gunCalibre
Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
-
D.
weaponCategory
chosen
Indicates the classification or type of weapon to which an item or armament belongs.
-
E.
lightArmament
Indicates that an entity is equipped with or characterized by relatively minimal or lightweight weaponry compared to standard or heavy armament.
- 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_69e24906fb108190a6898751e46bdc11 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b91364208190b3404534a7403e08 |
completed | April 29, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69f155e4b1148190836ede4741dcb888 |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7:07 p.m.