Triple
T25964030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Assault Weapons Ban |
E645614
|
entity |
| Predicate | affectedWeaponType |
P67648
|
FINISHED |
| Object | semiautomatic rifles |
—
|
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: semiautomatic rifles | Statement: [Federal Assault Weapons Ban, affectedWeaponType, semiautomatic rifles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectedWeaponType Context triple: [Federal Assault Weapons Ban, affectedWeaponType, semiautomatic rifles]
-
A.
usedWeapon
Indicates that an entity employed a specific weapon as the means or tool to carry out an action or event.
-
B.
relatedToWeaponType
chosen
Indicates that an entity has an association or connection with a specific type or category of weapon.
-
C.
associatedWithWeapon
Indicates that an entity has a connection or involvement with a weapon, such as ownership, use, presence, or relevance in a given context.
-
D.
weaponUsedAgainst
Indicates that a particular weapon or instrument is employed in an act of aggression, attack, or harm directed toward a specific target or entity.
-
E.
hasWeaponType
Indicates that an entity is associated with or equipped with a specific type or category of weapon.
- 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_69e77e85efc08190997da7fcf98bd300 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a731508190bb0c8c2462eba224 |
completed | May 2, 2026, 7:33 p.m. |
Created at: April 22, 2026, 8:48 a.m.