Triple

T15532015
Position Surface form Disambiguated ID Type / Status
Subject Giske E370242 entity
Predicate locatedInAdministrativeTerritory P40 FINISHED
Object Sunnmøre E367264 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: Sunnmøre | Statement: [Giske, locatedInAdministrativeTerritory, Sunnmøre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sunnmøre
Context triple: [Giske, locatedInAdministrativeTerritory, Sunnmøre]
  • A. Sunnmøre chosen
    Sunnmøre is a coastal district in western Norway known for its dramatic fjords, islands, and the fishing and maritime industries centered around towns like Ålesund.
  • B. Nordmøre
    Nordmøre is a traditional district in the northern part of Møre og Romsdal county in western Norway, known for its coastal landscapes, fjords, and fishing communities.
  • C. Romsdal
    Romsdal is a traditional district in Møre og Romsdal county in western Norway, known for its dramatic fjords, mountains, and the town of Molde.
  • D. Hattfjelldal
    Hattfjelldal is a sparsely populated municipality in Nordland county, Norway, known for its mountainous terrain, extensive wilderness areas, and strong Sami cultural heritage.
  • E. Fjordane
    Fjordane is a traditional district in western Norway known for its dramatic fjord landscapes and coastal scenery.
  • 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e0414877d88190804ee76566004e13 completed April 16, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00aade82788190a5f3cedbc22065c4 completed May 10, 2026, 3:57 p.m.
Created at: April 10, 2026, 4:06 a.m.