Triple

T14126808
Position Surface form Disambiguated ID Type / Status
Subject Dovrefjell E340054 entity
Predicate partOf P40 FINISHED
Object Dovre region E652822 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: Dovre region | Statement: [Dovrefjell, partOf, Dovre region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dovre region
Context triple: [Dovrefjell, partOf, Dovre region]
  • A. Dovre region chosen
    The Dovre region is a mountainous area in central Norway known for its rugged landscapes, national parks, and rich wildlife, including wild reindeer.
  • B. Nord-Valdres
    Nord-Valdres is the northern part of the traditional Valdres district in Innlandet county, Norway, known for its mountainous landscapes, valleys, and rural communities.
  • C. Trøndelag
    Trøndelag is a central region of Norway known for its historic city of Trondheim, coastal landscapes, and strong cultural traditions.
  • D. Sør-Valdres
    Sør-Valdres is a southern subregion of the traditional Valdres district in Innlandet county, Norway, known for its rural landscapes and mountain valleys.
  • E. Lillehammer region
    The Lillehammer region is an area in southeastern Norway known for its winter sports facilities, scenic landscapes, and role as host of the 1994 Winter Olympics.
  • 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_69d81c6a95b481909e39111e0c1f31ee completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de6098013c8190b1bac9d3fff60acd completed April 14, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe8bbd051c8190a89f9801a7b08b2d completed May 9, 2026, 1:19 a.m.
Created at: April 9, 2026, 10:22 p.m.