Triple

T3648648
Position Surface form Disambiguated ID Type / Status
Subject Karmøy E77362 entity
Predicate hasWrittenLanguageForm P13953 FINISHED
Object 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: Nynorsk | Statement: [Karmøy, hasWrittenLanguageForm, Nynorsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nynorsk
Context triple: [Karmøy, hasWrittenLanguageForm, 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. 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.
  • D. Bokmål
    Bokmål is the most widely used written standard of the Norwegian language, employed in government, education, media, and everyday communication.
  • E. Riksmål
    Riksmål is a traditional, conservative written standard of Norwegian closely aligned with Danish and used primarily by language purists and certain cultural institutions.
  • 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_69ad85de1b988190a45f8dbfebc806fc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc38c22548190a271a69fb832a5a8 completed March 8, 2026, 6:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b44f3c85348190b1d16179294f7f09 completed March 13, 2026, 5:54 p.m.
Created at: March 8, 2026, 3:24 p.m.