Triple

T21888621
Position Surface form Disambiguated ID Type / Status
Subject Markveien E540478 entity
Predicate locatedIn P40 FINISHED
Object Grünerløkka 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: Grünerløkka | Statement: [Markveien, locatedIn, Grünerløkka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grünerløkka
Context triple: [Markveien, locatedIn, Grünerløkka]
  • A. Grünerløkka district chosen
    Grünerløkka district is a trendy, centrally located neighborhood in Oslo known for its vibrant street life, cafes, bars, and creative cultural scene.
  • B. Blindern
    Blindern is the main campus area of the University of Oslo, known for housing several of its key faculties and academic buildings.
  • C. Frogner district
    Frogner district is an affluent central borough of Oslo, Norway, known for its historic architecture, embassies, and the famous Frogner Park with the Vigeland sculpture installation.
  • D. Haugaland district
    Haugaland district is a traditional region in western Norway centered around the coastal city of Haugesund and known for its maritime heritage and rugged coastal landscape.
  • E. Oslo East
    Oslo East is the eastern part of Norway’s capital city, often associated with working-class neighborhoods, cultural diversity, and a strong local football supporter culture.
  • 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_69e0c47a95908190ae3e19b716accb3d completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f118ee5f1c8190b8c6c431039eb8c9 completed April 28, 2026, 8:30 p.m.
Created at: April 16, 2026, 7:05 p.m.