Triple
T649711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mauser BK-27 |
E11318
|
entity |
| Predicate | rateOfFire |
P17731
|
FINISHED |
| Object | about 1700 rounds per minute |
—
|
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: about 1700 rounds per minute | Statement: [Mauser BK-27, rateOfFire, about 1700 rounds per minute]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rateOfFire Context triple: [Mauser BK-27, rateOfFire, about 1700 rounds per minute]
-
A.
fireModes
Indicates the different ways or settings in which a weapon or device can be fired or operated.
-
B.
gunCalibre
Indicates the relationship between a firearm and the calibre (size/diameter) of ammunition it is designed to use.
-
C.
ammunitionType
Indicates the specific kind or category of ammunition associated with or used by an entity.
-
D.
primaryArmament
Indicates the main weapon or principal offensive system that an entity (such as a vehicle, vessel, or platform) is equipped with or uses.
-
E.
weaponCapability
Indicates that one entity has the ability to use, deploy, or function as a weapon against another entity or target.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f31e70c81909a2ac1d939f7ec07 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0eade081909c47e85ed55f808d |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49df0de3c81909721eb391ec94031 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:36 p.m.