Triple

T5840367
Position Surface form Disambiguated ID Type / Status
Subject Slottsparken area E129576 entity
Predicate hasView P854 FINISHED
Object Oslo cityscape 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 cityscape | Statement: [Slottsparken area, hasView, Oslo cityscape]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oslo cityscape
Context triple: [Slottsparken area, hasView, Oslo cityscape]
  • A. Oslo chosen
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • B. Trondheim
    Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
  • C. Fjord City (Oslo waterfront redevelopment area)
    Fjord City is a major urban redevelopment project transforming Oslo’s waterfront into a modern district of housing, culture, business, and public spaces along the Oslofjord.
  • D. Majorstuen, Oslo
    Majorstuen is a central neighborhood in Oslo, Norway, known for its busy transport hub, shopping streets, and cultural institutions.
  • E. Sentrum, Oslo
    Sentrum is the central borough of Oslo, Norway, encompassing the city’s main downtown area, key commercial districts, and major transport hubs.
  • 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_69c0084af79c81908af128ccc29983d0 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c034d6f09c81908dfb3c2c51a2f5a9 completed March 22, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a19e4ec4819099fa5c6fe9a6a257 completed March 23, 2026, 2:12 a.m.
Created at: March 22, 2026, 3:54 p.m.