Triple

T5251385
Position Surface form Disambiguated ID Type / Status
Subject Kongsvinger E118595 entity
Predicate countyBefore2020 P52130 FINISHED
Object Hedmark E102451 NE FINISHED

How this triple was built (3 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: Hedmark | Statement: [Kongsvinger, countyBefore2020, Hedmark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hedmark
Context triple: [Kongsvinger, countyBefore2020, Hedmark]
  • A. Hedmark chosen
    Hedmark is a former county in eastern Norway known for its vast forests, agriculture, and inland landscapes along the Swedish border.
  • B. Hedmarken
    Hedmarken is a traditional district in Innlandet county in eastern Norway, known for its agricultural landscapes and its central town, Hamar.
  • C. Buskerud
    Buskerud is a former county in southeastern Norway known for its varied landscape of forests, rivers, and mountains, including parts of the Hallingdal valley and Hardangervidda plateau.
  • D. Sogn og Fjordane
    Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
  • E. Vestfold og Telemark
    Vestfold og Telemark is a former county in southeastern Norway known for its coastal towns, industrial heritage, and varied landscapes from fjords to inland forests and mountains.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: countyBefore2020
Context triple: [Kongsvinger, countyBefore2020, Hedmark]
  • A. countyAfter2020Reform
    Indicates that an administrative county exists in its form or status as defined following the 2020 reform.
  • B. existedAsCountyUntil chosen
    Indicates that an entity functioned with the status or designation of a county up to a specified end date or time period.
  • C. usedAsCountyNameUntil
    Indicates that an entity served as the official name of a county up to a specified point in time.
  • D. formerNameOfDistrict
    Indicates that one district previously had a different official name, which is the value linked by this predicate.
  • E. countyName
    Indicates the specific name assigned to a county in which an entity is located or with which it is associated.
  • F. None of above.

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_69bd446978108190bb5f9c5c23d93f88 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b7b840881908bb1ecb8a0047382 completed March 20, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfd7104f008190b2bcacc8d071277c completed March 22, 2026, 11:48 a.m.
PD Predicate disambiguation batch_69bd77c30bac8190a883ca45da35d667 completed March 20, 2026, 4:37 p.m.
Created at: March 20, 2026, 1:50 p.m.