Triple

T16027240
Position Surface form Disambiguated ID Type / Status
Subject Vågsøy E388746 entity
Predicate formerAdministrativeCentre P23608 FINISHED
Object Måløy 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: Måløy | Statement: [Vågsøy, formerAdministrativeCentre, Måløy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Måløy
Context triple: [Vågsøy, formerAdministrativeCentre, Måløy]
  • A. Måløy chosen
    Måløy is a coastal town in western Norway known as a key fishing port and regional commercial center.
  • B. Hisøy
    Hisøy is an island in southern Norway that forms part of the coastal region of Agder, known for its maritime character and proximity to the town of Arendal.
  • C. Dillingøy
    Dillingøy is an island located in southeastern Norway, within the coastal area of Moss in Østfold/Viken county.
  • D. Kvitsøy
    Kvitsøy is a small island municipality in southwestern Norway known for its maritime heritage, lighthouse, and rich coastal fishing grounds.
  • E. Holsnøy
    Holsnøy is a large island in Vestland county, Norway, known for its rugged coastal landscape and proximity to the city of Bergen.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e18328707c8190b9a444c78faaaa04 completed April 17, 2026, 12:47 a.m.
Created at: April 10, 2026, 4:56 a.m.