Triple

T5838358
Position Surface form Disambiguated ID Type / Status
Subject Ruter E129530 entity
Predicate servesRegion P82 FINISHED
Object Viken E93795 NE FINISHED

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: [Ruter, servesRegion, Viken]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viken
Context triple: [Ruter, servesRegion, 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. Skurusundet
    Skurusundet is a narrow strait in the Stockholm archipelago of Sweden, known for its scenic waterfront, bridges, and residential surroundings.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c0084af79c81908af128ccc29983d0 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c034a66c448190a6ea7f9827cbffe9 completed March 22, 2026, 6:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b0f371008190b11cd4da8a55dbb9 completed March 23, 2026, 3:18 a.m.
Created at: March 22, 2026, 3:54 p.m.