Triple

T6266137
Position Surface form Disambiguated ID Type / Status
Subject Fjord City E140417 entity
Predicate partOf P40 FINISHED
Object Oslo waterfront E149914 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 waterfront | Statement: [Fjord City, partOf, Oslo waterfront]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oslo waterfront
Context triple: [Fjord City, partOf, Oslo waterfront]
  • A. Aker Brygge chosen
    Aker Brygge is a popular waterfront district in Oslo known for its modern architecture, restaurants, shops, and vibrant harbor promenade.
  • B. Lyngseidet
    Lyngseidet is a small coastal village in northern Norway, known for its scenic fjord and mountain surroundings on the Lyngen Peninsula.
  • C. Kolsås
    Kolsås is a suburban area in Bærum, Norway, known as the endpoint of one of the Oslo Metro lines and for its nearby forested hill popular for hiking and climbing.
  • D. Stavanger harbor
    Stavanger harbor is a central Norwegian port area known for its maritime activity, cruise ship traffic, and role as a gateway to the North Sea oil industry and nearby fjords.
  • E. 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.
  • 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_69c51932e704819083e1ed17a86f6b5e completed March 26, 2026, 11:32 a.m.
Created at: March 22, 2026, 4:25 p.m.