Triple

T15463935
Position Surface form Disambiguated ID Type / Status
Subject Gomalandet E371975 entity
Predicate locatedInRegion P40 FINISHED
Object Nordmøre E380328 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: Nordmøre | Statement: [Gomalandet, locatedInRegion, Nordmøre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nordmøre
Context triple: [Gomalandet, locatedInRegion, Nordmøre]
  • A. Nordmøre chosen
    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.
  • B. Sunnmøre
    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.
  • 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. Dillingøy
    Dillingøy is an island located in southeastern Norway, within the coastal area of Moss in Østfold/Viken county.
  • 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_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f1927708190a0d2b63e75469a0e completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a001f7d79348190aba1889a7eb3d7c8 completed May 10, 2026, 6:02 a.m.
Created at: April 10, 2026, 3:33 a.m.