Triple

T21963521
Position Surface form Disambiguated ID Type / Status
Subject Kløfta Station E542397 entity
Predicate locatedInCounty P40 FINISHED
Object Viken 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: Viken | Statement: [Kløfta Station, locatedInCounty, Viken]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viken
Context triple: [Kløfta Station, locatedInCounty, Viken]
  • A. Viken chosen
    Viken is a county in southeastern Norway that includes the area around Oslo and stretches from the Swedish border to the mountainous interior.
  • B. Kattegat
    Kattegat is a shallow sea area and strait between Denmark and Sweden that forms a key maritime passage linking the North Sea with the Baltic Sea.
  • C. Sollentuna
    Sollentuna is a suburban town in Stockholm County, Sweden, known as part of the Stockholm urban area and a residential and commercial hub just north of the capital.
  • D. Torsken
    Torsken is a small coastal village and former fishing-based municipality located on the island of Senja in northern Norway.
  • E. Ostönnen
    Ostönnen is a village and district of the town of Soest in North Rhine-Westphalia, Germany.
  • 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.