Triple

T21066959
Position Surface form Disambiguated ID Type / Status
Subject Søre Ål parish E518999 entity
Predicate locatedIn P40 FINISHED
Object Lillehammer 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: Lillehammer | Statement: [Søre Ål parish, locatedIn, Lillehammer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lillehammer
Context triple: [Søre Ål parish, locatedIn, Lillehammer]
  • A. Lillehammer chosen
    Lillehammer is a Norwegian town in the Gudbrandsdalen valley, best known internationally for staging the 1994 Winter Olympics.
  • B. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • C. Tromsø
    Tromsø is a city in northern Norway known for its Arctic location, vibrant cultural scene, and prominence as a viewing spot for the Northern Lights.
  • D. Lørenskog
    Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
  • E. Alsvåg
    Alsvåg is a small coastal village in Nordland county, Norway, known for its fishing industry and scenic location within the municipality of Øksnes.
  • 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_69e0b505ef108190b25dd4033e2ff7eb completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6feb455fc81909cc63fa0e87b6a35 completed April 21, 2026, 4:36 a.m.
Created at: April 16, 2026, 2:45 p.m.