Triple

T7566263
Position Surface form Disambiguated ID Type / Status
Subject Hovedøya E178919 entity
Predicate partOf P40 FINISHED
Object Oslo municipality E3654 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 municipality | Statement: [Hovedøya, partOf, Oslo municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oslo municipality
Context triple: [Hovedøya, partOf, Oslo municipality]
  • A. Trondheim municipality
    Trondheim municipality is a local government area in Trøndelag county, Norway, encompassing the city of Trondheim and its surrounding districts.
  • B. Oslo chosen
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • C. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • D. Oslo City Council
    Oslo City Council is the elected municipal legislature responsible for setting policies, budgets, and regulations for the city of Oslo, Norway.
  • E. Oslo county
    Oslo county is Norway’s capital county, encompassing the city of Oslo and serving as the country’s political, economic, and cultural 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_69c69f2f80288190b95cceb4da92ab2b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8fde87c81909795fc713d7378ff completed March 27, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9061d1be0819094109703ec4a99f7 completed March 29, 2026, 10:59 a.m.
Created at: March 27, 2026, 3:50 p.m.