Triple

T15216542
Position Surface form Disambiguated ID Type / Status
Subject Fløibanen E363650 entity
Predicate intermediateStation P24280 FINISHED
Object Skansemyren
Skansemyren is a hillside area in Bergen, Norway, known for its residential neighborhoods and recreational facilities, including sports fields and access to hiking trails.
E1143512 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: Skansemyren | Statement: [Fløibanen, intermediateStation, Skansemyren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skansemyren
Context triple: [Fløibanen, intermediateStation, Skansemyren]
  • A. 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.
  • B. Møysalen
    Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
  • C. Baljåsen
    Baljåsen is a hill in western Sweden known as the highest natural point in the historical province of Dalsland.
  • D. Ormåsen
    Ormåsen is a small residential village in Øvre Eiker municipality in Buskerud county, Norway.
  • E. Svingvoll
    Svingvoll is a small village in Innlandet county, Norway, known for its rural setting and proximity to skiing and outdoor recreation areas.
  • 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: Skansemyren
Triple: [Fløibanen, intermediateStation, Skansemyren]
Generated description
Skansemyren is a hillside area in Bergen, Norway, known for its residential neighborhoods and recreational facilities, including sports fields and access to hiking trails.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Skansemyren
Target entity description: Skansemyren is a hillside area in Bergen, Norway, known for its residential neighborhoods and recreational facilities, including sports fields and access to hiking trails.
  • A. 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.
  • B. Møysalen
    Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
  • C. Baljåsen
    Baljåsen is a hill in western Sweden known as the highest natural point in the historical province of Dalsland.
  • D. Ormåsen
    Ormåsen is a small residential village in Øvre Eiker municipality in Buskerud county, Norway.
  • E. Svingvoll
    Svingvoll is a small village in Innlandet county, Norway, known for its rural setting and proximity to skiing and outdoor recreation areas.
  • 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_69d85a0ce24c81909c4d3b6475548c95 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0076f90c481909989befe031a2cae completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed343f51481908f04c35d37b39ad2 completed May 9, 2026, 6:25 a.m.
NEDg Description generation batch_69fed44b2e3c8190aad111e2bc2b56a2 completed May 9, 2026, 6:29 a.m.
NED2 Entity disambiguation (via description) batch_69fed547192c8190b89755fff48ca620 completed May 9, 2026, 6:33 a.m.
Created at: April 10, 2026, 3:11 a.m.