Triple

T14951668
Position Surface form Disambiguated ID Type / Status
Subject Fjaler E372807 entity
Predicate municipalCodeSystem P116809 FINISHED
Object Norwegian municipal number system 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: Norwegian municipal number system | Statement: [Fjaler, municipalCodeSystem, Norwegian municipal number system]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: municipalCodeSystem
Context triple: [Fjaler, municipalCodeSystem, Norwegian municipal number system]
  • A. hasMunicipalityCode
    Indicates that an entity is associated with a specific official municipality code used for administrative or identification purposes.
  • B. municipalKey
    Indicates a unique identifier that links an entity to a specific municipality within an administrative or geographic system.
  • C. hasMunicipalDistrictNumber
    Indicates that a municipality or local administrative unit is assigned a specific district number within its municipal structure.
  • D. hasLocalGovernmentCode
    Indicates that an entity is associated with a specific code assigned by a local government authority for identification or administrative purposes.
  • E. districtCode
    Indicates that an entity is associated with, or identified by, a specific administrative district code.
  • F. None of above. chosen

Provenance (4 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_69d85cca979481908747d2a81eba1cea completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded690f2e08190ad9dad6dc05a164a completed April 15, 2026, 12:06 a.m.
PD Predicate disambiguation batch_69de9a588c2c8190b1245a1c406f447c completed April 14, 2026, 7:49 p.m.
PDg Predicate description generation batch_69deb1a4d8dc8190a4c0841c20f2875f completed April 14, 2026, 9:29 p.m.
Created at: April 10, 2026, 2:39 a.m.