Triple

T6331632
Position Surface form Disambiguated ID Type / Status
Subject Nordre Aker E142393 entity
Predicate contains P35 FINISHED
Object Sinsen E148392 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 | Statement: [Nordre Aker, contains, Sinsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sinsen
Context triple: [Nordre Aker, contains, Sinsen]
  • A. Sinsen chosen
    Sinsen is a neighborhood and major transport hub in Oslo, Norway, known for its busy traffic interchange and public transit connections.
  • B. Oslo East
    Oslo East is the eastern part of Norway’s capital city, often associated with working-class neighborhoods, cultural diversity, and a strong local football supporter culture.
  • C. Ullensaker
    Ullensaker is a municipality in Viken county, Norway, best known for hosting Oslo Airport, Gardermoen, the country’s main international airport.
  • D. Drammen
    Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
  • E. Lysaker
    Lysaker is a key transport and business hub in the western part of the Oslo metropolitan area in Norway, featuring a major railway and commuter center.
  • 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_69c008d4d8e88190ad301c05b08722ac completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06514cbe8819096dbeb17ccb3e3d5 completed March 22, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a5cf7008190a24ecfeab5acb583 completed March 28, 2026, 12:01 a.m.
Created at: March 22, 2026, 4:30 p.m.