Triple
T4727600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of London Police |
E104923
|
entity |
| Predicate | followsPolicingModel |
P21773
|
FINISHED |
| Object | British policing by consent |
—
|
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: British policing by consent | Statement: [City of London Police, followsPolicingModel, British policing by consent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsPolicingModel Context triple: [City of London Police, followsPolicingModel, British policing by consent]
-
A.
policingModel
chosen
Indicates the approach, strategy, or framework used to organize and conduct policing activities or law enforcement operations.
-
B.
followsPolityOf
Indicates that one entity adopts, adheres to, or operates under the political system, governance model, or policy framework established by another entity.
-
C.
usedByLawEnforcementModel
Indicates that something is employed or utilized by law enforcement agencies or personnel, typically as a tool, method, or model in their operations or decision-making.
-
D.
typeOfLawEnforcement
Indicates that one entity is a specific kind or category of law enforcement associated with another entity.
-
E.
usesPolicyModel
Indicates that one entity applies, relies on, or operates according to a particular policy model.
- 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_69bd43ed84648190ae0b7ee8e8d00482 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6220071881909670c89d072ffb6d |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:18 p.m.