Triple

T22151027
Position Surface form Disambiguated ID Type / Status
Subject Kampen E547411 entity
Predicate locatedNear P294 FINISHED
Object Ensjø 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: Ensjø | Statement: [Kampen, locatedNear, Ensjø]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ensjø
Context triple: [Kampen, locatedNear, Ensjø]
  • A. Ensjø chosen
    Ensjø is a residential and former industrial neighborhood in Oslo, Norway, known for its ongoing urban redevelopment and good public transport connections.
  • B. Hemnessjøen
    Hemnessjøen is a lake in southeastern Norway that forms part of the Haldenvassdraget watercourse system.
  • C. Frøysjøen
    Frøysjøen is a coastal fjord or sea area in western Norway, situated below the towering cliff of Hornelen.
  • D. Drevsjø
    Drevsjø is a small village in Engerdal Municipality in Innlandet county, Norway, known for its forested surroundings, lakes, and outdoor recreation opportunities near the Swedish border.
  • E. Funnsjøen
    Funnsjøen is a lake located in the municipality of Meråker in Trøndelag county, central Norway.
  • 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_69e11e3b52088190ad5df386d01eb2fb completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129f37dac8190a7cecb12f4271515 completed April 28, 2026, 9:43 p.m.
Created at: April 16, 2026, 8:33 p.m.