Triple

T13798501
Position Surface form Disambiguated ID Type / Status
Subject Løten municipality E331577 entity
Predicate partOf P40 FINISHED
Object Hedmarken district E370730 NE 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: Hedmarken district | Statement: [Løten municipality, partOf, Hedmarken district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hedmarken district
Context triple: [Løten municipality, partOf, Hedmarken district]
  • A. Hedmark
    Hedmark is a former county in eastern Norway known for its vast forests, agriculture, and inland landscapes along the Swedish border.
  • B. Hedmarken chosen
    Hedmarken is a traditional district in Innlandet county in eastern Norway, known for its agricultural landscapes and its central town, Hamar.
  • C. Akershus county
    Akershus county was a former county in southeastern Norway that historically surrounded Oslo and included both urban suburbs and rural areas before being merged into Viken county.
  • D. Trøndelag County
    Trøndelag County is a large region in central Norway known for its historic city of Trondheim, coastal and fjord landscapes, and role as a cultural and economic hub of the country.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d81c58feb08190a77bca8bf7d6d20f completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de025ce9148190b23370f6a522ff7a completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a014132570081909fab220c002c2f10 completed May 11, 2026, 2:38 a.m.
Created at: April 9, 2026, 10:11 p.m.