Triple

T10505461
Position Surface form Disambiguated ID Type / Status
Subject Per Anger E247773 entity
Predicate burialPlace P196 FINISHED
Object Norra begravningsplatsen E18028 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: Norra begravningsplatsen | Statement: [Per Anger, burialPlace, Norra begravningsplatsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norra begravningsplatsen
Context triple: [Per Anger, burialPlace, Norra begravningsplatsen]
  • A. Norra begravningsplatsen chosen
    Norra begravningsplatsen is a major historic cemetery in Stockholm, Sweden, known as the final resting place of many prominent Swedish figures, including Alfred Nobel.
  • B. Vår Frelsers gravlund
    Vår Frelsers gravlund is a historic cemetery in Oslo, Norway, known as the resting place of many prominent Norwegian cultural and political figures.
  • C. Ytterhogdal cemetery
    Ytterhogdal cemetery is a burial ground in Ytterhogdal, Sweden, known as the final resting place of prominent silversmith and Romani rights activist Rosa Taikon.
  • D. Vålerenga Cemetery
    Vålerenga Cemetery is a burial ground located in the Vålerenga area of the Gamle Oslo borough in Oslo, Norway.
  • E. Vestre Toten
    Vestre Toten is a municipality in Innlandet county, Norway, known for its mix of rural landscapes, small towns, and industrial activity.
  • 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_69d381c4aa948190942e1d803143fb0e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509a07c908190bf0e3e5d480b306d completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dcd89ba481908653730b43e3d4ab completed April 10, 2026, 11:19 a.m.
Created at: April 6, 2026, 12:26 p.m.