Triple
T11462645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hitler’s buzzsaw |
E271698
|
entity |
| Predicate | refersToWeaponRateOfFire |
P17731
|
FINISHED |
| Object | approximately 1,200–1,500 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: approximately 1,200–1,500 rounds per minute | Statement: [Hitler’s buzzsaw, refersToWeaponRateOfFire, approximately 1,200–1,500 rounds per minute]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refersToWeaponRateOfFire Context triple: [Hitler’s buzzsaw, refersToWeaponRateOfFire, approximately 1,200–1,500 rounds per minute]
-
A.
rateOfFire
chosen
Indicates the frequency at which a weapon or system can discharge projectiles or shots over a given period of time.
-
B.
limitedWeaponType
Indicates that the use or availability of a weapon is restricted to a specific type or set of types.
-
C.
weaponCapability
Indicates that one entity has the ability to use, deploy, or function as a weapon against another entity or target.
-
D.
isServiceRifleOf
Indicates that one entity is the designated service rifle used by another entity, typically a military or armed force.
-
E.
typicalWeapon
Indicates that the object is a weapon commonly or characteristically used by the subject.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d822f488248190b9f603cd31c72174 |
completed | April 9, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69d80867ff248190bb157fa9e355353b |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:35 p.m.