Triple

T16263162
Position Surface form Disambiguated ID Type / Status
Subject Landsmål E394805 entity
Predicate codifiedBy P1115 FINISHED
Object Ivar Aasen E506888 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: Ivar Aasen | Statement: [Landsmål, codifiedBy, Ivar Aasen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ivar Aasen
Context triple: [Landsmål, codifiedBy, Ivar Aasen]
  • A. Ivar Aasen chosen
    Ivar Aasen was a Norwegian philologist, lexicographer, and poet best known for creating Nynorsk, one of the two official written standards of the Norwegian language.
  • B. Johan Ernst Gunnerus
    Johan Ernst Gunnerus was an 18th-century Norwegian bishop and naturalist renowned for his pioneering contributions to botany and for co-founding the Royal Norwegian Society of Sciences and Letters.
  • C. Erling Bjørnson
    Erling Bjørnson was a Norwegian farmer and politician, best known as the son of Nobel Prize–winning writer Bjørnstjerne Bjørnson.
  • D. Eilif Skodvin
    Eilif Skodvin is a Norwegian screenwriter and television creator best known for co-creating the crime-comedy series "Lilyhammer."
  • E. Eilif Peterssen
    Eilif Peterssen was a prominent Norwegian painter of the late 19th and early 20th centuries, known for his portraits, historical scenes, and landscapes.
  • 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_69d87f221d8081909b0b2063e7528ba2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e245c5583c8190901e892238cf8dbd completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a001f8eac988190bdcba6778fbffd64 completed May 10, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:04 a.m.