Triple

T6266144
Position Surface form Disambiguated ID Type / Status
Subject Fjord City E140417 entity
Predicate hasPart P35 FINISHED
Object Sørenga E562394 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: Sørenga | Statement: [Fjord City, hasPart, Sørenga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sørenga
Context triple: [Fjord City, hasPart, Sørenga]
  • A. Sørenga chosen
    Sørenga is a modern waterfront neighborhood in Oslo, Norway, known for its residential developments, seaside promenade, and popular public seawater pool and beach.
  • B. Sørreisa
    Sørreisa is a small coastal municipality and village area in northern Norway known for its fjords and rural Arctic landscape.
  • C. Ørskog
    Ørskog is a village and former municipality in western Norway, located in the county of Møre og Romsdal.
  • D. Sørkjosen
    Sørkjosen is a small coastal village in Northern Norway known as a gateway to the Reisa valley and Reisa National Park.
  • E. Mortensrud
    Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
  • 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_69c008cabc4081909723e2547c9d6cc0 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0639fdad081908492c44d369df8c5 completed March 22, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81e93671481909555acbc8a712930 completed March 28, 2026, 6:31 p.m.
Created at: March 22, 2026, 4:25 p.m.