Triple
T30730556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 69th Precinct |
E782409
|
entity |
| Predicate | policeServiceAreaType |
P68386
|
FINISHED |
| Object | precinct |
—
|
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: precinct | Statement: [69th Precinct, policeServiceAreaType, precinct]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policeServiceAreaType Context triple: [69th Precinct, policeServiceAreaType, precinct]
-
A.
areaTypePoliced
Indicates that a particular type of geographic or administrative area falls under the policing responsibility or jurisdiction of a specified policing entity.
-
B.
policeAreaPrecursorOf
Indicates that one police area served as a predecessor or earlier form of another police area in an administrative or organizational sequence.
-
C.
policeDepartmentType
Indicates the specific organizational category or classification of a police department (e.g., municipal, state, federal).
-
D.
localGovernmentAreaType
Indicates the specific classification or category of a local government area within an administrative or governmental hierarchy.
-
E.
areaServedType
chosen
Indicates the type or category of area that is served by an entity or service.
- 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_69f224ad9f9c81908e02a79ae0001137 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 29, 2026, 8:37 p.m.