Triple

T13413645
Position Surface form Disambiguated ID Type / Status
Subject Møysalen National Park E320152 entity
Predicate hasHighestPoint P210 FINISHED
Object Møysalen E317940 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: Møysalen | Statement: [Møysalen National Park, hasHighestPoint, Møysalen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Møysalen
Context triple: [Møysalen National Park, hasHighestPoint, Møysalen]
  • A. Møysalen chosen
    Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
  • B. Glåma
    Glåma is the longest and largest river in Norway, flowing through eastern parts of the country before emptying into the Oslofjord.
  • C. Mortensrud
    Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
  • D. Finnsnes
    Finnsnes is a small coastal town in northern Norway that serves as a commercial and transport hub for the island municipality of Senja.
  • E. Oppåkermoen
    Oppåkermoen is a small village located in the municipality of Nes in Akershus county, Norway.
  • 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_69d806b943cc8190b6af624d385d7e12 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaeb556948190af008c88e5bbf051 completed April 12, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7a83382e88190bfb229f9bab59b17 completed May 3, 2026, 7:55 p.m.
Created at: April 9, 2026, 9:35 p.m.