Triple

T8094446
Position Surface form Disambiguated ID Type / Status
Subject Sauda E188946 entity
Predicate locatedIn P40 FINISHED
Object Norwegian county of Rogaland E139000 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: Norwegian county of Rogaland | Statement: [Sauda, locatedIn, Norwegian county of Rogaland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norwegian county of Rogaland
Context triple: [Sauda, locatedIn, Norwegian county of Rogaland]
  • A. Rogaland chosen
    Rogaland is a county in southwestern Norway known for its rugged coastline, fjords, and the oil industry centered around the city of Stavanger.
  • B. Jæren region
    The Jæren region is a coastal area in southwestern Norway known for its flat, fertile farmland, long sandy beaches, and the city of Stavanger as its main urban center.
  • C. Sogn og Fjordane
    Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
  • D. Nordland county
    Nordland county is a long, coastal region in northern Norway known for its dramatic fjords, islands, and Arctic landscapes.
  • E. Hordaland
    Hordaland was a former county in western Norway known for its fjords, coastal landscapes, and the city of Bergen.
  • 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_69ca82b7b3e88190b9041ab0ef28b3cb completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb429089cc81909e4625f9cc7e305f completed March 31, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc64112138819096050975d707d8ee completed April 1, 2026, 12:17 a.m.
Created at: March 30, 2026, 5:30 p.m.