Triple

T5290841
Position Surface form Disambiguated ID Type / Status
Subject Flytoget E119736 entity
Predicate regionServed 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: [Flytoget, regionServed, Viken]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viken
Context triple: [Flytoget, regionServed, 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_69bd446de5648190b313a90bd96730d2 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84eac7b88190900142bd1310c0fd completed March 20, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf1880bec88190a5b1ca453c783444 completed March 21, 2026, 10:15 p.m.
Created at: March 20, 2026, 1:52 p.m.