Triple
T23685247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eagle Mountain, Utah |
E585146
|
entity |
| Predicate | publicSafetyServices |
P15991
|
FINISHED |
| Object | municipal police services |
—
|
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 services | Statement: [Eagle Mountain, Utah, publicSafetyServices, municipal police services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicSafetyServices Context triple: [Eagle Mountain, Utah, publicSafetyServices, municipal police services]
-
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.
safetyResponse
Indicates how an entity reacts or what measures it takes in response to a potential or actual safety-related situation.
-
C.
safety
Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
-
D.
safetyAdvice
Indicates that one entity provides guidance or recommendations to another entity about how to avoid danger or reduce risk in a particular context.
-
E.
safetyContext
Indicates the circumstances, conditions, or environment that affect how safe an action, object, or situation is.
- 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_69e249037ce0819088b149608e98f685 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b4fb26c88190a6776e4dfd10d54c |
completed | April 29, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f155d5265881908e43a9696b6a6d0f |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 6:52 p.m.