Triple

T21969221
Position Surface form Disambiguated ID Type / Status
Subject Aulestad E542540 entity
Predicate locatedNear P294 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: [Aulestad, locatedNear, Lillehammer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lillehammer
Context triple: [Aulestad, locatedNear, Lillehammer]
  • A. Lillehammer chosen
    Lillehammer is a Norwegian town in the Gudbrandsdalen valley, best known internationally for staging the 1994 Winter Olympics.
  • B. Lillehammer prosti
    Lillehammer prosti is a deanery within the Church of Norway that oversees several parishes in and around the town of Lillehammer.
  • C. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • D. 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.
  • E. Lørenskog
    Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
  • 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_69e0c48070988190909db97667b9a0ac completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1245d50d08190a4bf93139daa77eb completed April 28, 2026, 9:19 p.m.
Created at: April 16, 2026, 8:02 p.m.