Triple

T7275330
Position Surface form Disambiguated ID Type / Status
Subject Frognerseteren E163011 entity
Predicate partOf P40 FINISHED
Object Holmenkollen area E585824 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: Holmenkollen area | Statement: [Frognerseteren, partOf, Holmenkollen area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Holmenkollen area
Context triple: [Frognerseteren, partOf, Holmenkollen area]
  • A. Holmenkollen ski arena
    Holmenkollen ski arena is a famous Norwegian winter sports venue in Oslo, best known for its iconic ski jumping hill and hosting major international skiing competitions.
  • B. Kolsås ski slope
    Kolsås ski slope is a local alpine skiing and snowboarding area in the Kolsås hill region near Oslo, Norway.
  • C. Lillehammer Olympiapark
    Lillehammer Olympiapark is the organization that manages and maintains the sports venues and facilities built for the 1994 Winter Olympics in Lillehammer, Norway.
  • D. Kongsberg Ski Centre
    Kongsberg Ski Centre is a Norwegian winter sports facility known for its alpine skiing slopes and snowboarding terrain near the town of Kongsberg.
  • E. Holmenkollen Line chosen
    The Holmenkollen Line is a historic Oslo Metro line running into the hilly Holmenkollen area, known for serving ski resorts and residential neighborhoods in the city's northwest.
  • 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_69c6885c5964819085b209701769877f completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb0fd8788190aa21d4b2ad773926 completed March 27, 2026, 8:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7db2c76fc81909632c7ee4e54f81c completed March 28, 2026, 1:44 p.m.
Created at: March 27, 2026, 2:58 p.m.