Triple

T15243610
Position Surface form Disambiguated ID Type / Status
Subject Ranelva E364319 entity
Predicate locatedIn P40 FINISHED
Object Nordland county NE NERFINISHED

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: Nordland county | Statement: [Ranelva, locatedIn, Nordland county]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nordland county
Context triple: [Ranelva, locatedIn, Nordland county]
  • A. Nordland county chosen
    Nordland county is a long, coastal region in northern Norway known for its dramatic fjords, islands, and Arctic landscapes.
  • B. 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.
  • C. Møre og Romsdal
    Møre og Romsdal is a coastal county in western Norway known for its dramatic fjords, islands, and mountainous landscapes.
  • D. Helgeland district
    Helgeland district is a traditional region in southern Nordland county, Norway, known for its coastal archipelagos, fjords, and scattered rural communities.
  • E. Oppland
    Oppland is a former inland county in southeastern Norway known for its mountainous terrain, national parks, and popular skiing and hiking areas.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007dcc33081908545ea1a1d2c19fe completed April 15, 2026, 9:49 p.m.
Created at: April 10, 2026, 3:13 a.m.