Triple

T21963533
Position Surface form Disambiguated ID Type / Status
Subject Kløfta Station E542397 entity
Predicate connectsTo P845 FINISHED
Object Lillestrøm 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: Lillestrøm | Statement: [Kløfta Station, connectsTo, Lillestrøm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lillestrøm
Context triple: [Kløfta Station, connectsTo, Lillestrøm]
  • A. Lillestrøm chosen
    Lillestrøm is a Norwegian town and former municipality in the Greater Oslo Region, known as a regional commercial center and transport hub.
  • B. Lillestrøm SK
    Lillestrøm SK is a Norwegian professional football club known for its passionate fan base, historic success in domestic competitions, and intense rivalry with other Oslo-area teams.
  • C. Mjøndalen
    Mjøndalen is a town in Viken county, Norway, known historically for its industry and for its football club Mjøndalen IF.
  • D. Vålerenga
    Vålerenga is a neighborhood in Oslo, Norway, known for its working-class roots and strong association with the local football club Vålerenga Fotball.
  • E. Strømsgodset
    Strømsgodset is a Norwegian professional football club based in Drammen, best known for competing in the country’s top division, the Eliteserien.
  • 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_69e0c47fab1081908dc74a6545dbb051 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f12458e4488190a04f8d3958854b49 completed April 28, 2026, 9:19 p.m.
Created at: April 16, 2026, 8:01 p.m.