Triple

T15412525
Position Surface form Disambiguated ID Type / Status
Subject Hardangervidda National Park E368627 entity
Predicate mainAccessTown P22318 FINISHED
Object Geilo E433543 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: Geilo | Statement: [Hardangervidda National Park, mainAccessTown, Geilo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Geilo
Context triple: [Hardangervidda National Park, mainAccessTown, Geilo]
  • A. Geilo chosen
    Geilo is a Norwegian mountain village and popular year-round resort known for its skiing, hiking, and proximity to the Hardangervidda plateau.
  • B. Giæver
    Giæver is a Norwegian surname borne by several notable figures in fields such as physics, literature, and public service.
  • C. Bjorli
    Bjorli is a Norwegian village known for its ski resort and scenic mountain surroundings in Innlandet county.
  • D. Giske
    Giske is a coastal municipality in Møre og Romsdal county, Norway, known for its islands, fishing communities, and proximity to the town of Ålesund.
  • E. Lohberg
    Lohberg is a small Bavarian village in the Bavarian Forest region of Germany, known as a gateway to outdoor activities around the Großer Arber mountain.
  • 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_69d85a16c68c819099c1b547fbc87b32 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03ea600b48190a3dbca1a68a2a1cd completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a754d1881909ed322479bab460d completed May 9, 2026, 11:28 a.m.
Created at: April 10, 2026, 3:20 a.m.