Triple

T12293594
Position Surface form Disambiguated ID Type / Status
Subject Lørenskog E293027 entity
Predicate partOf P40 FINISHED
Object Oslo metropolitan area E229565 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: Oslo metropolitan area | Statement: [Lørenskog, partOf, Oslo metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oslo metropolitan area
Context triple: [Lørenskog, partOf, Oslo metropolitan area]
  • A. Greater Oslo Region chosen
    The Greater Oslo Region is the metropolitan area surrounding Norway’s capital, encompassing Oslo and its neighboring municipalities as a unified economic and commuter region.
  • B. Bergens
    The Bergens are a race of gloomy, troll-eating creatures who serve as the primary villains in the animated film "Trolls."
  • C. Oslo
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • D. Oslo
    Oslo is a collection of shared libraries that provide common code and patterns used across various OpenStack projects.
  • E. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • 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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91d23def88190adbaa282dd03d6c6 completed April 10, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c62e40481908a688912055c697c completed May 2, 2026, 10:36 p.m.
Created at: April 8, 2026, 9:52 p.m.