Triple

T19403646
Position Surface form Disambiguated ID Type / Status
Subject Slottsfjellet E485392 entity
Predicate hasPart P35 FINISHED
Object Slottsfjellstårnet NE NERFINISHED

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: Slottsfjellstårnet | Statement: [Slottsfjellet, hasPart, Slottsfjellstårnet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Slottsfjellstårnet
Context triple: [Slottsfjellet, hasPart, Slottsfjellstårnet]
  • A. Slottsfjellet chosen
    Slottsfjellet is a historic hill and former fortress site in Tønsberg, Norway, known for its medieval castle ruins and prominent tower overlooking the city.
  • B. Årdalstangen
    Årdalstangen is a village in Vestland county, Norway, known for its industrial activity and location at the end of the Årdalsfjorden.
  • C. Preikestolen
    Preikestolen is a famous steep cliff and viewpoint in southwestern Norway that towers over the Lysefjord and attracts many hikers and tourists.
  • D. Beitostølen
    Beitostølen is a Norwegian mountain village and popular year-round tourist destination known for its skiing, hiking, and access to the Jotunheimen National Park.
  • E. Hafjell
    Hafjell is a major Norwegian ski resort in the Øyer municipality, known for hosting alpine events during the 1994 Lillehammer Winter Olympics and offering extensive slopes and winter sports facilities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d5162481909db12435d9535c1a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6257937d081909dbc5804d2505938 completed April 20, 2026, 1:09 p.m.
Created at: April 10, 2026, 1:36 p.m.