Triple

T22962407
Position Surface form Disambiguated ID Type / Status
Subject Gamle Bybro E570936 entity
Predicate connects P390 FINISHED
Object Bakklandet E570933 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: Bakklandet | Statement: [Gamle Bybro, connects, Bakklandet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bakklandet
Context triple: [Gamle Bybro, connects, Bakklandet]
  • A. Bakklandet chosen
    Bakklandet is a historic, picturesque neighborhood in Trondheim, Norway, known for its colorful wooden houses, cobbled streets, and riverside cafés.
  • B. Bekkelaget
    Bekkelaget is a coastal residential neighborhood in Oslo, Norway, known for its hillside views over the Oslofjord and its traditional wooden houses.
  • C. Kalbakken
    Kalbakken is a residential neighborhood in Oslo, Norway, known for its apartment blocks, green areas, and access to public transportation.
  • D. Haugalandet
    Haugalandet is a coastal region in western Norway centered around the town of Haugesund, known for its maritime heritage and North Sea industries.
  • E. Enebakk
    Enebakk is a rural municipality in Viken county, Norway, known for its forests, lakes, and proximity to the Oslo metropolitan area.
  • 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_69e245b212a88190b5259caf51606084 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f181f594fc8190816418486b798198 completed April 29, 2026, 3:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c0ac534d88190bd369b8e608b3ddc completed May 19, 2026, 7:01 a.m.
Created at: April 17, 2026, 3:47 p.m.