Triple

T18413678
Position Surface form Disambiguated ID Type / Status
Subject Uppsala old cemetery E441830 entity
Predicate hasNotableBurials P3803 FINISHED
Object Karin Boye NE NERFINISHED

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: Karin Boye | Statement: [Uppsala old cemetery, hasNotableBurials, Karin Boye]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karin Boye
Context triple: [Uppsala old cemetery, hasNotableBurials, Karin Boye]
  • A. Karin Boye chosen
    Karin Boye was a prominent 20th-century Swedish poet and novelist, best known for her lyrical poetry and the dystopian novel "Kallocain."
  • B. Sissel Kyrkjebø
    Sissel Kyrkjebø is a Norwegian soprano renowned for her crystal-clear voice and wide-ranging repertoire spanning classical, folk, and pop music.
  • C. Lene Andersen
    Lene Andersen is a Danish author and futurist known for her work on democracy, ethics, and societal development.
  • D. Pernilla Wahlgren
    Pernilla Wahlgren is a Swedish singer, actress, and television personality known for her long career in entertainment and frequent appearances in music, theater, and TV shows.
  • E. Ghita Nørby
    Ghita Nørby is a renowned Danish actress celebrated for her extensive film, television, and theater career, making her one of Denmark’s most prominent and respected performers.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9eb8a508190a942fd75ebd8b1dc completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e51a259c1c819094e710bb4a7ace75 completed April 19, 2026, 6:08 p.m.
Created at: April 10, 2026, 10:47 a.m.