Triple

T3593314
Position Surface form Disambiguated ID Type / Status
Subject Hjørundfjord E76077 entity
Predicate locatedIn P40 FINISHED
Object Møre og Romsdal county E114915 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: Møre og Romsdal county | Statement: [Hjørundfjord, locatedIn, Møre og Romsdal county]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Møre og Romsdal county
Context triple: [Hjørundfjord, locatedIn, Møre og Romsdal county]
  • A. Møre og Romsdal chosen
    Møre og Romsdal is a coastal county in western Norway known for its dramatic fjords, islands, and mountainous landscapes.
  • B. Nordland county
    Nordland county is a long, coastal region in northern Norway known for its dramatic fjords, islands, and Arctic landscapes.
  • C. Sogn og Fjordane
    Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
  • D. Oppland
    Oppland is a former inland county in southeastern Norway known for its mountainous terrain, national parks, and popular skiing and hiking areas.
  • E. Rogaland
    Rogaland is a county in southwestern Norway known for its rugged coastline, fjords, and the oil industry centered around the city of Stavanger.
  • 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_69ad85d8042081908af94a04c410dec0 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc15bbbcc81908d6cf95f8e70c6ca completed March 8, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a81fdf888190a4d9f75471b9ec39 completed March 14, 2026, 6:25 p.m.
Created at: March 8, 2026, 3:22 p.m.