Triple

T15555681
Position Surface form Disambiguated ID Type / Status
Subject Geiranger E370860 entity
Predicate hasViewpoint P854 FINISHED
Object Dalsnibba
Dalsnibba is a high mountain viewpoint in Norway famous for its panoramic views over the Geirangerfjord and surrounding alpine landscape.
E1164037 NE FINISHED

How this triple was built (4 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: Dalsnibba | Statement: [Geiranger, hasViewpoint, Dalsnibba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dalsnibba
Context triple: [Geiranger, hasViewpoint, Dalsnibba]
  • A. Dælenenga
    Dælenenga is an area in Oslo, Norway, known for its sports facilities and urban character within the inner-city district.
  • B. Dalsgrenda
    Dalsgrenda is a small settlement located within Rana Municipality in Nordland county, Norway.
  • C. Stöllet
    Stöllet is a small locality in central Sweden situated within Torsby Municipality in Värmland County.
  • D. Lögberg
    Lögberg is the historic Law Rock at Þingvellir in Iceland, where the Althing, one of the world’s oldest parliaments, traditionally convened and laws were proclaimed.
  • E. Thamerdal
    Thamerdal is a residential neighborhood within the Dutch town of Uithoorn in the province of North Holland.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Dalsnibba
Triple: [Geiranger, hasViewpoint, Dalsnibba]
Generated description
Dalsnibba is a high mountain viewpoint in Norway famous for its panoramic views over the Geirangerfjord and surrounding alpine landscape.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dalsnibba
Target entity description: Dalsnibba is a high mountain viewpoint in Norway famous for its panoramic views over the Geirangerfjord and surrounding alpine landscape.
  • A. Dælenenga
    Dælenenga is an area in Oslo, Norway, known for its sports facilities and urban character within the inner-city district.
  • B. Dalsgrenda
    Dalsgrenda is a small settlement located within Rana Municipality in Nordland county, Norway.
  • C. Stöllet
    Stöllet is a small locality in central Sweden situated within Torsby Municipality in Värmland County.
  • D. Lögberg
    Lögberg is the historic Law Rock at Þingvellir in Iceland, where the Althing, one of the world’s oldest parliaments, traditionally convened and laws were proclaimed.
  • E. Thamerdal
    Thamerdal is a residential neighborhood within the Dutch town of Uithoorn in the province of North Holland.
  • F. None of above. chosen

Provenance (5 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04a97dbfc8190a98cbbac5e71ba88 completed April 16, 2026, 2:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff456427988190bddea01f5cb159d9 completed May 9, 2026, 2:32 p.m.
NEDg Description generation batch_69ff470492f48190852ede832157ed10 completed May 9, 2026, 2:39 p.m.
NED2 Entity disambiguation (via description) batch_69ff47e5647c81909b785a1212c4bc50 completed May 9, 2026, 2:42 p.m.
Created at: April 10, 2026, 4:09 a.m.