Triple

T6331659
Position Surface form Disambiguated ID Type / Status
Subject Nordre Aker E142393 entity
Predicate hasGreenArea P5383 FINISHED
Object Grefsenkollen E553432 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: Grefsenkollen | Statement: [Nordre Aker, hasGreenArea, Grefsenkollen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grefsenkollen
Context triple: [Nordre Aker, hasGreenArea, Grefsenkollen]
  • A. Grefsen chosen
    Grefsen is a residential neighborhood in Oslo, Norway, known for its hillside location with views over the city and access to public transport and green areas.
  • B. Kållerado
    Kållerado is a popular river rapids ride at the Liseberg amusement park in Gothenburg, Sweden.
  • C. Gruvbyn
    Gruvbyn is a historic mining village area on the island of Utö in Sweden, known for its old iron ore mines and traditional archipelago settlement.
  • D. Telegrafberget
    Telegrafberget is a prominent hill in the Södertörn region of Sweden, known as its highest natural point and a notable local viewpoint.
  • E. Storvreten
    Storvreten is a residential locality within Botkyrka Municipality in the Stockholm County area of Sweden.
  • 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_69c008d4d8e88190ad301c05b08722ac completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0651634b08190b54860ba0a70f5c4 completed March 22, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6041f713c8190b27ba54181049377 completed March 27, 2026, 4:14 a.m.
Created at: March 22, 2026, 4:30 p.m.