Triple
T8131012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AR-15 pattern rifles |
E189850
|
entity |
| Predicate | hasMagazineCapacityRange |
P25151
|
FINISHED |
| Object | typically 5 to 30 rounds |
—
|
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: typically 5 to 30 rounds | Statement: [AR-15 pattern rifles, hasMagazineCapacityRange, typically 5 to 30 rounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMagazineCapacityRange Context triple: [AR-15 pattern rifles, hasMagazineCapacityRange, typically 5 to 30 rounds]
-
A.
ammunitionCapacity
chosen
Indicates the maximum amount of ammunition that something (typically a weapon or container) is designed to hold at one time.
-
B.
hasChamber
Indicates that one entity possesses, contains, or is associated with a distinct enclosed space or compartment (a chamber).
-
C.
armamentCapacity
Indicates the maximum quantity or type of weapons or munitions that something is designed or allowed to carry.
-
D.
hasChamberLength
Indicates the length measurement of a chamber associated with an entity.
-
E.
hasChamberWidth
Indicates that an entity possesses a chamber whose width has a specified value or range.
- 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_69ca82bcb4848190a9a9d036ad768642 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4c4c2e388190b86854f8b1765e61 |
completed | March 31, 2026, 4:23 a.m. |
| PD | Predicate disambiguation | batch_69cb3696379c8190a20965e59ed8f370 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:34 p.m.