Triple

T33713317
Position Surface form Disambiguated ID Type / Status
Subject Langhus E863801 entity
Predicate countyPreviouslyPartOf P110432 FINISHED
Object Akershus county 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 county | Statement: [Langhus, countyPreviouslyPartOf, Akershus county]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: countyPreviouslyPartOf
Context triple: [Langhus, countyPreviouslyPartOf, Akershus county]
  • A. hasFormerCounty chosen
    Indicates that an entity was previously part of, or administered by, a particular county in the past but no longer is.
  • B. formerMunicipalityOf
    Indicates that an entity was previously an independent municipality that has since been merged into or replaced by the referenced municipality.
  • C. previousCounty
    Indicates that one county was the immediately preceding county associated with an entity before the current or later county.
  • D. formerNameOfAreaWithin
    Indicates that one area previously had a different name while remaining within the same larger encompassing area.
  • E. formerProvinceMunicipality
    Indicates that a municipality previously held the status of a province-level administrative unit but no longer does.
  • 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_69f3498844608190bb8f9b14908d2510 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_6a00c9ddd62881909859a36b114a4132 completed May 10, 2026, 6:09 p.m.
PD Predicate disambiguation batch_6a00c939b88881909d5353db4265e572 completed May 10, 2026, 6:06 p.m.
Created at: May 1, 2026, 1:43 a.m.