Triple

T16028782
Position Surface form Disambiguated ID Type / Status
Subject Helgeland E388787 entity
Predicate hasSubregion P285 FINISHED
Object Inner Helgeland E388787 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: Inner Helgeland | Statement: [Helgeland, hasSubregion, Inner Helgeland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Inner Helgeland
Context triple: [Helgeland, hasSubregion, Inner Helgeland]
  • A. Helgeland chosen
    Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
  • B. Nordre Land
    Nordre Land is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and agricultural landscape in the traditional district of Land.
  • C. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • D. Bømlafjorden region
    The Bømlafjorden region is a coastal fjord area in western Norway known for its maritime landscape, islands, and traditional fishing communities.
  • E. Breheimen region
    The Breheimen region is a mountainous area in western Norway known for its rugged peaks, glaciers, and inclusion in the Breheimen National Park.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1832a56ec8190a47fd2cf83a42fd4 completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf33c6a881909284933ea3b7dd6e completed May 10, 2026, 12:20 a.m.
Created at: April 10, 2026, 4:56 a.m.