Triple

T3882318
Position Surface form Disambiguated ID Type / Status
Subject Galdhøpiggen E92852 entity
Predicate hasMountainHutNearby P15807 FINISHED
Object Spiterstulen E398069 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: Spiterstulen | Statement: [Galdhøpiggen, hasMountainHutNearby, Spiterstulen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Spiterstulen
Context triple: [Galdhøpiggen, hasMountainHutNearby, Spiterstulen]
  • A. Spiterstulen chosen
    Spiterstulen is a mountain lodge in Norway’s Jotunheimen region that serves as a key base for hikers and climbers exploring nearby peaks.
  • B. Stetind
    Stetind is a distinctive, obelisk-shaped granite mountain in Nordland, Norway, often called Norway’s national mountain and renowned among climbers and photographers.
  • C. Higravstinden
    Higravstinden is a prominent mountain peak in Norway’s Lofoten archipelago, known for its rugged alpine terrain and striking coastal views.
  • D. Storslett
    Storslett is a small village and administrative center in Nordreisa Municipality in Troms og Finnmark county in northern Norway.
  • E. Egertorget
    Egertorget is a central public square and popular meeting point in downtown Oslo, Norway, known for its shops, street life, and role as a hub along the city’s main thoroughfare.
  • 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_69aed9697de0819087c2559295ff3d12 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeec8e8b3481909617ca0e37f8a6d4 completed March 9, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b52845684c8190b6f0676319a6fc3c completed March 14, 2026, 9:20 a.m.
Created at: March 9, 2026, 3:20 p.m.