Triple
T36078580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jimmy "The Tulip" Tudeski |
E1043565
|
entity |
| Predicate | notableWeaponUse |
P204721
|
FINISHED |
| Object | firearms |
—
|
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: firearms | Statement: [Jimmy "The Tulip" Tudeski, notableWeaponUse, firearms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableWeaponUse Context triple: [Jimmy "The Tulip" Tudeski, notableWeaponUse, firearms]
-
A.
notableWeaponUsedNearby
Indicates that a notable weapon was used in close spatial or situational proximity to the referenced entity or event.
-
B.
hasNotableWeaponNamedAfter
Indicates that an entity possesses a notable weapon that is named after another specific entity.
-
C.
weaponUsedIn
Indicates that a particular weapon is employed or involved in carrying out a specific event or action.
-
D.
weaponUsedOn
Indicates that a particular weapon was employed or applied against a specific target or entity.
-
E.
notableAttack
Indicates that an entity carried out, was involved in, or is strongly associated with a particularly significant or well-known attack.
- 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_69f76e3154908190a6f702671c2bea08 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0895b48190acdd88dc10db7be7 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:08 p.m.