Triple

T13471705
Position Surface form Disambiguated ID Type / Status
Subject mainland Norway E311642 entity
Predicate contains P35 FINISHED
Object Hallingdal E107387 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: Hallingdal | Statement: [mainland Norway, contains, Hallingdal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hallingdal
Context triple: [mainland Norway, contains, Hallingdal]
  • A. Hallingdal chosen
    Hallingdal is a major valley and traditional district in southeastern Norway, known for its river, ski resorts, and rich folk culture.
  • B. Glåmdalen
    Glåmdalen is a valley region in Eastern Norway known for the Glomma River and its surrounding agricultural and forested landscapes.
  • C. Brumunddal
    Brumunddal is a town in Ringsaker Municipality in Innlandet county, Norway, known as an administrative and commercial center on the eastern shore of Lake Mjøsa.
  • D. Nissedal
    Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
  • E. Valldal
    Valldal is a village in western Norway known for its scenic fjord landscape and strawberry farming, situated in the county of Møre og Romsdal.
  • 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_69d806a938b8819097ec43a2229fc7f9 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf22e5f88190b1078f006c8ef7c0 completed April 12, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7547f6b1c8190965b239da0b47e93 completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:42 p.m.