Triple

T16509942
Position Surface form Disambiguated ID Type / Status
Subject Nordland E401032 entity
Predicate contains P35 FINISHED
Object Lofoten 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: Lofoten | Statement: [Nordland, contains, Lofoten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lofoten
Context triple: [Nordland, contains, Lofoten]
  • A. Lofoten chosen
    Lofoten is a dramatic Arctic archipelago in Norway known for its steep mountains, sheltered bays, fishing villages, and views of the midnight sun and Northern Lights.
  • B. Vesterålen
    Vesterålen is a scenic archipelago in northern Norway known for its dramatic coastal landscapes, rich fishing traditions, and excellent whale-watching opportunities.
  • C. Hamarøy
    Hamarøy is a coastal municipality in Nordland county, Norway, known for its dramatic fjord and mountain landscapes and its association with author Knut Hamsun.
  • D. Ålesund archipelago
    The Ålesund archipelago is a coastal island group in western Norway known for its scenic seascapes, fishing communities, and proximity to the Art Nouveau town of Ålesund.
  • E. Andøya
    Andøya is a large Norwegian island in Nordland county, known for its dramatic coastal landscapes, space center, and rich bird and whale-watching opportunities.
  • 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_69d88381f6148190819958a038be990e completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e54f7508190804bbae4c9bc8fe3 completed April 18, 2026, 7:10 a.m.
Created at: April 10, 2026, 5:14 a.m.