Triple

T17732026
Position Surface form Disambiguated ID Type / Status
Subject Namdalen E442609 entity
Predicate hasPart P35 FINISHED
Object Høylandet E592934 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: Høylandet | Statement: [Namdalen, hasPart, Høylandet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Høylandet
Context triple: [Namdalen, hasPart, Høylandet]
  • A. Høylandet chosen
    Høylandet is a rural municipality in Trøndelag county, Norway, known for its forested landscapes, agriculture, and small village communities.
  • B. Høyblokka
    Høyblokka is a prominent modernist high-rise government office building in central Oslo, Norway, known for housing key parts of the Norwegian government.
  • C. Hjelset
    Hjelset is a village in Møre og Romsdal county, Norway, situated within Molde Municipality along the Romsdalsfjorden.
  • D. Haugalandet
    Haugalandet is a coastal region in western Norway centered around the town of Haugesund, known for its maritime heritage and North Sea industries.
  • E. Dølen
    Dølen was a 19th-century Norwegian weekly periodical, written in Landsmål by Aasmund Olavsson Vinje, that combined literary works with social and political commentary.
  • 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_69d8b9ec79688190b86bdcef85a7b3aa completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e478e7773081909dadb90ff5cb0906 completed April 19, 2026, 6:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0242f577ac8190bc6c258ed79c0f3f completed May 11, 2026, 8:58 p.m.
Created at: April 10, 2026, 10:08 a.m.