Triple

T1229357
Position Surface form Disambiguated ID Type / Status
Subject Sentrum E26400 entity
Predicate contains P35 FINISHED
Object Aker Brygge E149914 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: Aker Brygge | Statement: [Sentrum, contains, Aker Brygge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aker Brygge
Context triple: [Sentrum, contains, Aker Brygge]
  • A. Aker Brygge chosen
    Aker Brygge is a popular waterfront district in Oslo known for its modern architecture, restaurants, shops, and vibrant harbor promenade.
  • B. Vestre Aker district
    Vestre Aker district is a largely affluent, residential borough in the western part of Oslo, Norway, known for its green areas and suburban character.
  • C. Frogner district
    Frogner district is an affluent central borough of Oslo, Norway, known for its historic architecture, embassies, and the famous Frogner Park with the Vigeland sculpture installation.
  • D. Ullensaker
    Ullensaker is a municipality in Viken county, Norway, best known for hosting Oslo Airport, Gardermoen, the country’s main international airport.
  • E. Kolsås
    Kolsås is a suburban area in Bærum, Norway, known as the endpoint of one of the Oslo Metro lines and for its nearby forested hill popular for hiking and climbing.
  • 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_69a4948571c88190a9191e451e6035fd completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be3dac2c8190914ff27173bb6b34 completed March 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc61b45748190a12e1aec029b76df completed March 8, 2026, 12:43 a.m.
Created at: March 1, 2026, 7:47 p.m.