Triple
T32548791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oslo Police District |
E831917
|
entity |
| Predicate | hasTelephoneNumberType |
P143303
|
FINISHED |
| Object | emergency number 112 (Norway) |
—
|
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: emergency number 112 (Norway) | Statement: [Oslo Police District, hasTelephoneNumberType, emergency number 112 (Norway)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTelephoneNumberType Context triple: [Oslo Police District, hasTelephoneNumberType, emergency number 112 (Norway)]
-
A.
hasTelephoneService
Indicates that a subject is provided with or connected to telephone service.
-
B.
telephoneAccessNumberType
chosen
Indicates the classification or category of a telephone access number, such as the type of service or access method it represents.
-
C.
hasContactMethod
Indicates that an entity has a specific way or channel through which it can be contacted.
-
D.
hasContactType
Indicates the specific kind or category of contact relationship that exists between two entities.
-
E.
hasWorkNumberType
Indicates that an entity’s work-related phone number is classified as a specific type (e.g., mobile, landline, extension).
- 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_69f34925fd08819084cfe4ec566cb704 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd44474ed48190ac372e4c88d762ed |
completed | May 8, 2026, 2:02 a.m. |
| PD | Predicate disambiguation | batch_69fd41ef28a48190a66959be5c964461 |
completed | May 8, 2026, 1:52 a.m. |
Created at: May 1, 2026, 1:02 a.m.