Triple
T15613266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LAPD Crime Suppression Platoons |
E375350
|
entity |
| Predicate | usesPolicingStrategy |
P13064
|
FINISHED |
| Object | data-driven deployment |
—
|
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: data-driven deployment | Statement: [LAPD Crime Suppression Platoons, usesPolicingStrategy, data-driven deployment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPolicingStrategy Context triple: [LAPD Crime Suppression Platoons, usesPolicingStrategy, data-driven deployment]
-
A.
usesStrategy
chosen
Indicates that an entity intentionally applies a particular strategy or method to achieve a goal or perform an action.
-
B.
usedPolicy
Indicates that an entity applied or followed a particular policy in carrying out an action or decision.
-
C.
usesPolicyModel
Indicates that one entity applies, relies on, or operates according to a particular policy model.
-
D.
establishedPolicy
Indicates that a policy has been formally created, adopted, and put into effect as a guiding rule or standard.
-
E.
policingModel
Indicates the approach, strategy, or framework used to organize and conduct policing activities or law enforcement operations.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e8148a0819087d6d69cc84487ca |
completed | April 16, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69deda844af081909e658ebc9d9b403d |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:13 a.m.