Triple

T1089859
Position Surface form Disambiguated ID Type / Status
Subject Österåker Municipality E24136 entity
Predicate hasCountrySubdivisionType P9832 FINISHED
Object county 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: county | Statement: [Österåker Municipality, hasCountrySubdivisionType, county]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCountrySubdivisionType
Context triple: [Österåker Municipality, hasCountrySubdivisionType, county]
  • A. countrySubdivisionType chosen
    Indicates the specific type or category of an administrative or territorial subdivision within a country (e.g., state, province, region).
  • B. hasSubdivisionCode
    Indicates that an entity is associated with a specific code identifying one of its internal subdivisions (such as a state, province, or region).
  • C. hasSubdivision
    Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
  • D. countrySubdivision
    Indicates that one geopolitical region is an administrative or territorial subdivision of a larger country.
  • E. countrySubdivisionStandardLink
    Indicates a reference or link to the standard or authoritative specification that defines the country’s internal subdivisions.
  • 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_69a49404428c819092dcc9632f5f7b8b completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b97f216881909e9b8943ce2078e4 completed March 1, 2026, 10:11 p.m.
PD Predicate disambiguation batch_69a4b741b0cc8190be001a16a81f6d9e completed March 1, 2026, 10:01 p.m.
Created at: March 1, 2026, 7:42 p.m.