Triple
T16941201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dublin Metropolitan Police District |
E410952
|
entity |
| Predicate | hasPoliceForceType |
P90046
|
FINISHED |
| Object | civilian, unarmed police |
—
|
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: civilian, unarmed police | Statement: [Dublin Metropolitan Police District, hasPoliceForceType, civilian, unarmed police]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPoliceForceType Context triple: [Dublin Metropolitan Police District, hasPoliceForceType, civilian, unarmed police]
-
A.
hasOwnPoliceForce
Indicates that an entity maintains and controls its own dedicated police force or law enforcement agency.
-
B.
hasPoliceInstitution
Indicates that an entity is associated with, governed by, or served by a particular police institution or law enforcement body.
-
C.
policeForceCharacteristic
chosen
Indicates that a specified characteristic, quality, or attribute is associated with a particular police force.
-
D.
hasPoliceDepartment
Indicates that an entity possesses, is served by, or is administratively associated with a police department.
-
E.
hasPolicePartner
Indicates that one entity has another entity as its partner in a police or law-enforcement context.
- 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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cfadec70819095ec0048ebc71016 |
completed | April 18, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_69e32b9aa8748190b248890aca86753d |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:31 a.m.