Triple

T5652563
Position Surface form Disambiguated ID Type / Status
Subject Dovre Line E124538 entity
Predicate passesThroughCounty P4247 FINISHED
Object Innlandet E65742 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: Innlandet | Statement: [Dovre Line, passesThroughCounty, Innlandet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Innlandet
Context triple: [Dovre Line, passesThroughCounty, Innlandet]
  • A. Innlandet chosen
    Innlandet is a county in eastern Norway known for its inland landscapes, including mountains, forests, and important winter sports venues.
  • B. Innlandet
    Innlandet is an island district of the Norwegian town of Kristiansund, known for its traditional wooden houses and coastal maritime character.
  • C. Hadeland
    Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
  • 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. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • 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_69c00825df388190a58742fa9b1aa33d completed March 22, 2026, 3:17 p.m.
NER Named-entity recognition batch_69c022d8a2588190b10de59edbc8841f completed March 22, 2026, 5:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a255f348190abe3c09fe0b38f45 completed March 22, 2026, 9:07 p.m.
Created at: March 22, 2026, 3:42 p.m.