Triple

T13953812
Position Surface form Disambiguated ID Type / Status
Subject Femundsmarka National Park E335602 entity
Predicate locatedIn P40 FINISHED
Object Trøndelag county 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: Trøndelag county | Statement: [Femundsmarka National Park, locatedIn, Trøndelag county]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trøndelag county
Context triple: [Femundsmarka National Park, locatedIn, Trøndelag county]
  • A. Trøndelag County chosen
    Trøndelag County is a large region in central Norway known for its historic city of Trondheim, coastal and fjord landscapes, and role as a cultural and economic hub of the country.
  • B. Hedmark
    Hedmark is a former county in eastern Norway known for its vast forests, agriculture, and inland landscapes along the Swedish border.
  • C. Sogn og Fjordane
    Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
  • D. Trøndelag
    Trøndelag is a central region of Norway known for its historic city of Trondheim, coastal landscapes, and strong cultural traditions.
  • E. Hedmarken
    Hedmarken is a traditional district in Innlandet county in eastern Norway, known for its agricultural landscapes and its central town, Hamar.
  • 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_69d81c6081b88190b53e317c3370c8fe completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e146720819085d0f5eae558b7a4 completed April 14, 2026, 12:07 p.m.
Created at: April 9, 2026, 10:17 p.m.