Triple

T1380821
Position Surface form Disambiguated ID Type / Status
Subject Bokmål E29332 entity
Predicate coOfficialWith P3084 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: [Bokmål, coOfficialWith, Nynorsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nynorsk
Context triple: [Bokmål, coOfficialWith, 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. 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.
  • C. Bokmål
    Bokmål is the most widely used written standard of the Norwegian language, employed in government, education, media, and everyday communication.
  • D. Riksmål
    Riksmål is a traditional, conservative written standard of Norwegian closely aligned with Danish and used primarily by language purists and certain cultural institutions.
  • E. Trøndersk dialect
    The Trøndersk dialect is a group of Norwegian dialects spoken in the Trøndelag region, known for its distinctive pronunciation, vocabulary, and grammatical features within Norwegian.
  • 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_69a498d883a48190bfdca525296ef7ee completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c319f46481909ba8a69a19b865e5 completed March 1, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69acd48a48fc81908b156c273cb5dfc0 completed March 8, 2026, 1:44 a.m.
Created at: March 1, 2026, 7:59 p.m.