Triple

T6401700
Position Surface form Disambiguated ID Type / Status
Subject Sagene district E144077 entity
Predicate hasNeighbouringBorough P16160 FINISHED
Object Frogner E126347 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: Frogner | Statement: [Sagene district, hasNeighbouringBorough, Frogner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frogner
Context triple: [Sagene district, hasNeighbouringBorough, Frogner]
  • A. Frogner district chosen
    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.
  • B. Frogner Park
    Frogner Park is a large public park in Oslo, Norway, best known for housing the Vigeland installation, the world’s largest sculpture park created by a single artist.
  • C. Vålerenggata
    Vålerenggata is a street located in the Vålerenga neighborhood of Oslo, Norway, known for its traditional wooden houses and historic urban character.
  • D. Blindern
    Blindern is the main campus area of the University of Oslo, known for housing several of its key faculties and academic buildings.
  • E. Toftes gate
    Toftes gate is a notable street in the Grünerløkka district of Oslo, Norway, known for its mix of historic buildings, cafes, and urban neighborhood life.
  • 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_69c008dc56fc81908d43ffcc11d73bdd completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c068ade8c881908a0472f1de6b7c21 completed March 22, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640bee09481908bdd0462f7cc43ff completed March 27, 2026, 8:33 a.m.
Created at: March 22, 2026, 4:35 p.m.