Triple

T33673687
Position Surface form Disambiguated ID Type / Status
Subject Skogrand E862695 entity
Predicate hasSecondarySubdivisionName P53398 FINISHED
Object Akershus NE NERFINISHED

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: Akershus | Statement: [Skogrand, hasSecondarySubdivisionName, Akershus]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasSecondarySubdivisionName
Context triple: [Skogrand, hasSecondarySubdivisionName, Akershus]
  • A. hasSecondLevelAdministrativeTerritory chosen
    Indicates that an entity possesses or includes a second-level administrative division within its territorial or organizational hierarchy.
  • B. hasSubdivisionName3
    Indicates that an entity has a third-level subdivision whose name is given by the associated value.
  • C. hasHigherLevelSubdivision
    Indicates that one administrative or organizational unit is contained within and subordinate to a larger, higher-level subdivision.
  • D. hasPrimaryCountrySubdivision
    Indicates that an entity is associated with a main or principal first-level administrative division (such as a state, province, or region) within a specific country.
  • E. hasSubdivision
    Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
  • 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_69f34985885c8190914322f492e04703 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69ff878f41888190bcb3bc41ad26081a completed May 9, 2026, 7:14 p.m.
PD Predicate disambiguation batch_69ff854082d88190aad3bfedf05e849f completed May 9, 2026, 7:04 p.m.
Created at: May 1, 2026, 1:43 a.m.