Triple
T28301644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General Duties Branch |
E713723
|
entity |
| Predicate | primaryPersonnelType |
P11881
|
FINISHED |
| Object | uniformed police officers |
—
|
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: uniformed police officers | Statement: [General Duties Branch, primaryPersonnelType, uniformed police officers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryPersonnelType Context triple: [General Duties Branch, primaryPersonnelType, uniformed police officers]
-
A.
personnelType
chosen
Indicates the classification or role category assigned to a person within an organization or system.
-
B.
personType
Indicates that an entity is classified as a particular type or category of person.
-
C.
standardPersonnel
Indicates that a person is recognized as regular or officially designated staff within an organization or context.
-
D.
primaryUserType
Indicates the main or dominant category of user associated with an entity or interaction.
-
E.
personnel
Indicates that an entity serves as staff or workforce associated with another entity, such as an organization, project, or facility.
- 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_69efb524ab688190a1ce7ee7c9520932 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_6a002249ee388190a9501ee7630dc658 |
completed | May 10, 2026, 6:14 a.m. |
| PD | Predicate disambiguation | batch_6a002189273881909b6b687e2d61f5b1 |
completed | May 10, 2026, 6:11 a.m. |
Created at: April 27, 2026, 11:35 p.m.