Triple
T12610954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sterling Heights Police Department |
E301118
|
entity |
| Predicate | hasOperationalAreaType |
P794
|
FINISHED |
| Object | municipality |
—
|
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: municipality | Statement: [Sterling Heights Police Department, hasOperationalAreaType, municipality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOperationalAreaType Context triple: [Sterling Heights Police Department, hasOperationalAreaType, municipality]
-
A.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
B.
operatesWithin
chosen
Indicates that one entity carries out its activities, functions, or operations inside the scope, boundaries, or jurisdiction defined by another entity.
-
C.
hasStudyAreaType
Indicates that an entity’s study area is classified as a specific type or category (e.g., lab, field site, classroom).
-
D.
hasPrimaryServiceArea
Indicates that an entity is associated with a main geographic or functional area in which it primarily provides its services.
-
E.
hasPlayAreaType
Indicates the specific kind or category of play area associated with an entity (e.g., indoor, outdoor, playground type).
- 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9559458dc8190bc4d6e697e99d70e |
completed | April 10, 2026, 7:55 p.m. |
| PD | Predicate disambiguation | batch_69d9541894fc8190a0c3706a414279f0 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 9, 2026, 5:11 p.m.