Triple

T19008959
Position Surface form Disambiguated ID Type / Status
Subject Telemark county E465165 entity
Predicate containsMunicipality P852 FINISHED
Object Fyresdal 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: Fyresdal | Statement: [Telemark county, containsMunicipality, Fyresdal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fyresdal
Context triple: [Telemark county, containsMunicipality, Fyresdal]
  • A. Fyresdal chosen
    Fyresdal is a rural municipality in Telemark county, Norway, known for its forests, lakes, and traditional farming communities.
  • B. Fagernes
    Fagernes is a small town in central Norway that serves as a regional hub and gateway to the mountainous Valdres district.
  • C. Tyssedal
    Tyssedal is a small industrial village in Vestland county, Norway, known for its historic hydropower facilities and scenic location by the Sørfjorden.
  • D. Flesberg
    Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
  • E. Norddal
    Norddal is a small village and former municipality in Møre og Romsdal county in western Norway, situated in the Sunnmøre region.
  • 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_69d8dd025c188190a1d81f5b4ec7e2c6 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d6a72aa88190a04f13cd14ee77d4 completed April 20, 2026, 7:32 a.m.
Created at: April 10, 2026, 12:02 p.m.