Triple

T13866010
Position Surface form Disambiguated ID Type / Status
Subject Lillehammer region E333328 entity
Predicate hasSkiResort P1981 FINISHED
Object Kvitfjell E444660 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: Kvitfjell | Statement: [Lillehammer region, hasSkiResort, Kvitfjell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kvitfjell
Context triple: [Lillehammer region, hasSkiResort, Kvitfjell]
  • A. Kvitfjell chosen
    Kvitfjell is a Norwegian alpine ski resort renowned for hosting major international competitions, including Olympic and World Cup events.
  • B. Filefjell
    Filefjell is a mountainous area and historic mountain pass in southern Norway, known as an important route between Eastern and Western Norway and a popular destination for hiking and winter sports.
  • C. Hodnefjell
    Hodnefjell is an island that forms part of the Finnøy archipelago in Norway.
  • D. Norefjell
    Norefjell is a prominent Norwegian mountain range and ski resort area known for its alpine terrain and winter sports facilities.
  • E. Slottsfjellet
    Slottsfjellet is a historic hill and former fortress site in Tønsberg, Norway, known for its medieval castle ruins and prominent tower overlooking the city.
  • 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_69d81c5ced9c8190b0e9bcc6effe5959 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de05c419d481909230e8879b6dab5c completed April 14, 2026, 9:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69fcdef1e4608190a137f340e06d5ddb completed May 7, 2026, 6:50 p.m.
Created at: April 9, 2026, 10:14 p.m.