Triple
T739249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Birmingham Police Department |
E15205
|
entity |
| Predicate | policeAgencyType |
P15991
|
FINISHED |
| Object | municipal 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: municipal police | Statement: [Birmingham Police Department, policeAgencyType, municipal police]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policeAgencyType Context triple: [Birmingham Police Department, policeAgencyType, municipal police]
-
A.
publicSafetyAgencyType
chosen
Indicates the specific category or kind of public safety agency associated with an entity (e.g., police, fire, emergency medical services).
-
B.
hasPoliceDepartment
Indicates that an entity possesses, is served by, or is administratively associated with a police department.
-
C.
policePrecinct
Indicates that a specified location, building, or area functions as or is designated as a police precinct.
-
D.
typeOfLawEnforcement
Indicates that one entity is a specific kind or category of law enforcement associated with another entity.
-
E.
securityAgency
Indicates that one entity functions as a security agency responsible for protection, surveillance, or enforcement activities in relation to another entity.
- 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_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a64adf2c81908e48090be35dd9d9 |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fc734c81908fbd36386d5746d6 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.