Triple

T15759839
Position Surface form Disambiguated ID Type / Status
Subject Kolltveit E382065 entity
Predicate regionLanguage P10892 FINISHED
Object Norwegian Nynorsk E92855 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 Nynorsk | Statement: [Kolltveit, regionLanguage, Norwegian Nynorsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norwegian Nynorsk
Context triple: [Kolltveit, regionLanguage, Norwegian Nynorsk]
  • A. Nynorsk chosen
    Nynorsk is one of the two official written standards of the Norwegian language, based primarily on rural and western Norwegian dialects.
  • B. Middle Norwegian
    Middle Norwegian is a historical North Germanic language stage spoken in Norway roughly between the late Middle Ages and the early modern period, bridging Old Norwegian and modern Norwegian.
  • C. New Norwegian
    New Norwegian is one of the two official written standards of the Norwegian language, developed in the 19th century from rural Norwegian dialects.
  • D. Norwegian language
    Norwegian is a North Germanic language spoken primarily in Norway, closely related to Danish and Swedish and featuring two official written standards, Bokmål and Nynorsk.
  • E. Bokmål
    Bokmål is the most widely used written standard of the Norwegian language, employed in government, education, media, and everyday communication.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e050b35ea48190a758ee76a57b5451 completed April 16, 2026, 3 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffbe66d78c81908308fc16c8d4e19c completed May 9, 2026, 11:08 p.m.
Created at: April 10, 2026, 4:47 a.m.