Triple

T6592395
Position Surface form Disambiguated ID Type / Status
Subject Sinsen E148392 entity
Predicate hasStructure P35 FINISHED
Object Sinsen roundabout E599686 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: Sinsen roundabout | Statement: [Sinsen, hasStructure, Sinsen roundabout]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sinsen roundabout
Context triple: [Sinsen, hasStructure, Sinsen roundabout]
  • A. Sinsen Interchange chosen
    Sinsen Interchange is a major multi-level road junction in Oslo, Norway, serving as a key traffic hub connecting several important highways and city routes.
  • B. Slussen
    Slussen is a major transport hub and metro station in central Stockholm, serving as a key interchange between multiple subway lines and other public transit.
  • C. Lillestrøm junction
    Lillestrøm junction is a major Norwegian railway interchange where multiple lines converge near the town of Lillestrøm, serving as an important hub in the Oslo region rail network.
  • D. Tøyen Torg
    Tøyen Torg is a central square and commercial hub in Oslo’s Tøyen neighborhood, known for its shops, cafés, and multicultural urban atmosphere.
  • E. Kungsportsavenyen
    Kungsportsavenyen is a major boulevard and central thoroughfare in Gothenburg, Sweden, known for its shops, restaurants, and cultural venues.
  • 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_69c687e7b8688190811ffee72e096468 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aece1f848190a11676e072afb002 completed March 27, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d57bde388190919ff6820e1b9610 completed March 27, 2026, 7:07 p.m.
Created at: March 27, 2026, 1:55 p.m.