Triple

T17180155
Position Surface form Disambiguated ID Type / Status
Subject Vannøya E416959 entity
Predicate hasLanguage P15 FINISHED
Object Norwegian E4355 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 | Statement: [Vannøya, hasLanguage, Norwegian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norwegian
Context triple: [Vannøya, hasLanguage, Norwegian]
  • A. Bokmål
    Bokmål is the most widely used written standard of the Norwegian language, employed in government, education, media, and everyday communication.
  • B. 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.
  • C. Norwegian Landsmål
    Norwegian Landsmål is a historical written standard of the Norwegian language that later developed into what is now known as Nynorsk.
  • D. Norwegian (administrative)
    Norwegian (administrative) is the official form of the Norwegian language used for government, legal, and bureaucratic purposes in certain territories such as Greenland and Svalbard.
  • E. Norwegian language chosen
    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.
  • 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_69d886d5f34c8190b24564dfaa63f3fb completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3fc10afb48190a71f4a46f0280a14 completed April 18, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a014847a19481909b1249c2fe428bfc completed May 11, 2026, 3:08 a.m.
Created at: April 10, 2026, 5:37 a.m.