Triple

T4365609
Position Surface form Disambiguated ID Type / Status
Subject Oppland E98763 entity
Predicate hasMajorTown P316 FINISHED
Object Fagernes E360440 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: Fagernes | Statement: [Oppland, hasMajorTown, Fagernes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fagernes
Context triple: [Oppland, hasMajorTown, Fagernes]
  • A. Fagernes chosen
    Fagernes is a small town in central Norway that serves as a regional hub and gateway to the mountainous Valdres district.
  • B. Finnås
    Finnås is a village and former church-centered parish on the island municipality of Bømlo in Vestland county, Norway.
  • C. Bolnes
    Bolnes is a Dutch surname most notably associated with Catharina Bolnes, the wife of painter Johannes Vermeer.
  • D. Mortensrud
    Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
  • E. Finnsnes
    Finnsnes is a small coastal town in northern Norway that serves as a commercial and transport hub for the island municipality of Senja.
  • 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_69b3454c772081908e20173e379e8ebe completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35200263081909bb326a4d7a8db99 completed March 12, 2026, 11:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b650be7ac88190a8476b956e5994ec completed March 15, 2026, 6:25 a.m.
Created at: March 12, 2026, 11:17 p.m.