Triple

T7765844
Position Surface form Disambiguated ID Type / Status
Subject Akersneset E176142 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: [Akersneset, partOf, Oslo waterfront]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oslo waterfront
Context triple: [Akersneset, 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_69c69962923c8190ac74d28b4f9fe0a0 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7043279748190b30882e9cc6cca54 completed March 27, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8c7e1a1408190a802d4f4afb8dd05 completed March 29, 2026, 6:34 a.m.
Created at: March 27, 2026, 4:09 p.m.