Triple
T31867145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Special Operations Division (Orange County Sheriff’s Office) |
E813486
|
entity |
| Predicate | operationRoutineLevel |
P201184
|
FINISHED |
| Object | non-routine |
—
|
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: non-routine | Statement: [Special Operations Division (Orange County Sheriff’s Office), operationRoutineLevel, non-routine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operationRoutineLevel Context triple: [Special Operations Division (Orange County Sheriff’s Office), operationRoutineLevel, non-routine]
-
A.
operation
Indicates that one entity performs, carries out, or controls the functioning of another entity or system.
-
B.
operatorDuringOperation
Indicates that an operator is the one performing or responsible for an operation during its execution.
-
C.
operateIn
Indicates that an entity performs its activities, functions, or services within a specified location, context, or domain.
-
D.
operate
Indicates that an agent performs, manages, or controls the functioning of a system, device, or process.
-
E.
operationScale
Indicates the relative size, scope, or magnitude at which an operation or activity is conducted.
- 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_69f348ecb07481909c8f72619131b115 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ffdd05d1908190957deb11392f4595 |
completed | May 10, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69ffdc0d33c881908b3483bee8a96540 |
completed | May 10, 2026, 1:14 a.m. |
| PDg | Predicate description generation | batch_69ffdd0486e08190a0f2ff4ce0aee13b |
completed | May 10, 2026, 1:19 a.m. |
Created at: April 30, 2026, 11:54 p.m.