Triple

T6216523
Position Surface form Disambiguated ID Type / Status
Subject Rogaland E139000 entity
Predicate hasRegion P285 FINISHED
Object Ryfylke E329313 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: Ryfylke | Statement: [Rogaland, hasRegion, Ryfylke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ryfylke
Context triple: [Rogaland, hasRegion, Ryfylke]
  • A. Ryfylke chosen
    Ryfylke is a traditional district in southwestern Norway known for its fjords, islands, and mountainous coastal landscape in Rogaland county.
  • B. 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.
  • C. 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.
  • D. 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.
  • E. Nordre Land
    Nordre Land is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and agricultural landscape in the traditional district of Land.
  • 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_69c008aecb0c81909984b48f733ce8ae completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062a1eb3881908c7f735cf9c429ce completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c518ff27848190817ad516cf62c619 completed March 26, 2026, 11:31 a.m.
Created at: March 22, 2026, 4:21 p.m.