Triple

T18114104
Position Surface form Disambiguated ID Type / Status
Subject MS Fæmund II E433556 entity
Predicate locatedNear P294 FINISHED
Object Røros region 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: Røros region | Statement: [MS Fæmund II, locatedNear, Røros region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Røros region
Context triple: [MS Fæmund II, locatedNear, Røros region]
  • A. Røros region chosen
    The Røros region is a historic mining area in central Norway known for its well-preserved wooden townscape and UNESCO-listed cultural heritage.
  • B. Trysil region
    Trysil region is a mountainous forested area in eastern Norway known for its large ski resort and outdoor recreation opportunities.
  • C. Dovre region
    The Dovre region is a mountainous area in central Norway known for its rugged landscapes, national parks, and rich wildlife, including wild reindeer.
  • D. Lyngen region
    The Lyngen region is a scenic area in Troms, northern Norway, known for its dramatic fjords, alpine peaks, and popular outdoor activities like skiing and hiking.
  • E. Bodø region
    The Bodø region is a coastal area in Northern Norway centered around the city of Bodø, known for its Arctic landscape, maritime industries, and role as a regional hub for education, transport, and commerce.
  • 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_69d8b90916008190a1f110bd7ced5473 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ddd4c7888190b85c39decdb0333f completed April 19, 2026, 1:51 p.m.
Created at: April 10, 2026, 10:28 a.m.