Triple

T3579320
Position Surface form Disambiguated ID Type / Status
Subject Vestland E75761 entity
Predicate borders P224 FINISHED
Object Møre og Romsdal 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 | Statement: [Vestland, borders, Møre og Romsdal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Møre og Romsdal
Context triple: [Vestland, borders, Møre og Romsdal]
  • 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. Sogn og Fjordane
    Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
  • C. Rogaland
    Rogaland is a county in southwestern Norway known for its rugged coastline, fjords, and the oil industry centered around the city of Stavanger.
  • D. Hordaland
    Hordaland was a former county in western Norway known for its fjords, coastal landscapes, and the city of Bergen.
  • E. Trøndelag
    Trøndelag is a central region of Norway known for its historic city of Trondheim, coastal landscapes, and strong cultural traditions.
  • 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_69ad85d5e3008190bdfe0bacdd1f5a1b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0ffecdc8190bf01c8ba90e3733e completed March 8, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69b56b2bcadc819093b827a28e3e8930 completed March 14, 2026, 2:05 p.m.
Created at: March 8, 2026, 3:21 p.m.