Triple

T15091954
Position Surface form Disambiguated ID Type / Status
Subject Fagernes E360440 entity
Predicate locatedNear P294 FINISHED
Object Filefjell E1064459 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: Filefjell | Statement: [Fagernes, locatedNear, Filefjell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Filefjell
Context triple: [Fagernes, locatedNear, Filefjell]
  • A. Filefjell chosen
    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.
  • B. Kvitfjell
    Kvitfjell is a Norwegian alpine ski resort renowned for hosting major international competitions, including Olympic and World Cup events.
  • C. Hodnefjell
    Hodnefjell is an island that forms part of the Finnøy archipelago in Norway.
  • D. 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.
  • E. Fjell
    Fjell was a former municipality in Vestland county, Norway, encompassing coastal and island communities west of Bergen.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0027925788190b955fdc6626adf7d completed April 15, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd24523081908cf12a5d6bdd634d completed May 9, 2026, 7:07 a.m.
Created at: April 10, 2026, 3:04 a.m.