Triple
T34871104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Empire in Kenya region |
E1005753
|
entity |
| Predicate | usedPoliceForce |
P86939
|
FINISHED |
| Object | Kenya Police |
—
|
NE NERFINISHED |
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: Kenya Police | Statement: [British Empire in Kenya region, usedPoliceForce, Kenya Police]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedPoliceForce Context triple: [British Empire in Kenya region, usedPoliceForce, Kenya Police]
-
A.
policeControl
Indicates that one entity exercises authoritative oversight, regulation, or enforcement power over another, as a police force does over people or areas under its jurisdiction.
-
B.
requiredPoliceProtection
Indicates that one entity needed or was assigned police protection in relation to another entity or situation.
-
C.
hasOwnPoliceForce
chosen
Indicates that an entity maintains and controls its own dedicated police force or law enforcement agency.
-
D.
stanceOnLawEnforcement
Indicates a subject’s position, attitude, or level of support regarding law enforcement practices, policies, or institutions.
-
E.
lawEnforcementResponse
Indicates the actions or measures taken by law enforcement agencies in reaction to an incident, behavior, or situation.
- 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_69f76dbde1c08190a24e7f9beb564c8d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.