Triple

T3517929
Position Surface form Disambiguated ID Type / Status
Subject Hardangerfjord E74351 entity
Predicate hasNearbyWaterfall P13549 FINISHED
Object Vøringsfossen
Vøringsfossen is one of Norway’s most famous and dramatic waterfalls, plunging into the Måbødalen valley in the Hardanger region.
E365825 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: Vøringsfossen | Statement: [Hardangerfjord, hasNearbyWaterfall, Vøringsfossen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vøringsfossen
Context triple: [Hardangerfjord, hasNearbyWaterfall, Vøringsfossen]
  • A. Bøylefoss
    Bøylefoss is a small settlement in the municipality of Froland in southern Norway, known historically for its waterfall and associated hydroelectric power development.
  • B. Sognsvann
    Sognsvann is a popular recreational lake and surrounding forested area in northern Oslo, Norway, known for hiking, swimming, and outdoor activities.
  • C. Fosnavåg
    Fosnavåg is a small coastal town in western Norway known for its maritime industries and scenic North Sea surroundings.
  • 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. Møysalen
    Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
  • 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: Vøringsfossen
Triple: [Hardangerfjord, hasNearbyWaterfall, Vøringsfossen]
Generated description
Vøringsfossen is one of Norway’s most famous and dramatic waterfalls, plunging into the Måbødalen valley in the Hardanger region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vøringsfossen
Target entity description: Vøringsfossen is one of Norway’s most famous and dramatic waterfalls, plunging into the Måbødalen valley in the Hardanger region.
  • A. Bøylefoss
    Bøylefoss is a small settlement in the municipality of Froland in southern Norway, known historically for its waterfall and associated hydroelectric power development.
  • B. Sognsvann
    Sognsvann is a popular recreational lake and surrounding forested area in northern Oslo, Norway, known for hiking, swimming, and outdoor activities.
  • C. Fosnavåg
    Fosnavåg is a small coastal town in western Norway known for its maritime industries and scenic North Sea surroundings.
  • 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. Møysalen
    Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
  • 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_69ad85cfb5c881909c9a2edd9d6043cc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc32f90081908960acb3e94402be completed March 8, 2026, 6:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e80cd588190ae012f151ef59c52 completed March 13, 2026, 3:03 a.m.
NEDg Description generation batch_69b37ef902208190842ddbe6427ca42b completed March 13, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_69b382b43b708190be7ae3d44b0a393a completed March 13, 2026, 3:21 a.m.
Created at: March 8, 2026, 3:19 p.m.