Triple
T28889113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caledon Hockley |
E732645
|
entity |
| Predicate | usesFirearm |
P7135
|
FINISHED |
| Object | pistol |
—
|
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: pistol | Statement: [Caledon Hockley, usesFirearm, pistol]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesFirearm Context triple: [Caledon Hockley, usesFirearm, pistol]
-
A.
usesFirearmsUnit
Indicates that one entity employs or operates firearms as part of a specific unit or organizational grouping.
-
B.
weaponUsedIn
Indicates that a particular weapon is employed or involved in carrying out a specific event or action.
-
C.
gun
chosen
Indicates that one entity uses, carries, or is associated with a gun in relation to another entity or 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.
firearmActionType
Indicates the specific type or category of action performed with or by a firearm (such as firing, loading, carrying, or modifying).
- 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_69f05b07bdec819080cadfe147aa1f25 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 28, 2026, 7:53 a.m.