Triple

T14881763
Position Surface form Disambiguated ID Type / Status
Subject Dalsland E350016 entity
Predicate hasHighestPoint P210 FINISHED
Object Baljåsen
Baljåsen is a hill in western Sweden known as the highest natural point in the historical province of Dalsland.
E1125726 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: Baljåsen | Statement: [Dalsland, hasHighestPoint, Baljåsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baljåsen
Context triple: [Dalsland, hasHighestPoint, Baljåsen]
  • A. Follebu
    Follebu is a village in Innlandet county, Norway, known for its rural setting and traditional Norwegian countryside character within Gausdal municipality.
  • B. Ormåsen
    Ormåsen is a small residential village in Øvre Eiker municipality in Buskerud county, Norway.
  • C. Jordal
    Jordal is a neighborhood in Oslo, Norway, known for its sports facilities and ice hockey heritage.
  • D. Bekkestua
    Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
  • E. Skutvik
    Skutvik is a small coastal village in Hamarøy Municipality in Nordland county, Norway, known as a ferry port linking the mainland with the Lofoten Islands.
  • 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: Baljåsen
Triple: [Dalsland, hasHighestPoint, Baljåsen]
Generated description
Baljåsen is a hill in western Sweden known as the highest natural point in the historical province of Dalsland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Baljåsen
Target entity description: Baljåsen is a hill in western Sweden known as the highest natural point in the historical province of Dalsland.
  • A. Follebu
    Follebu is a village in Innlandet county, Norway, known for its rural setting and traditional Norwegian countryside character within Gausdal municipality.
  • B. Ormåsen
    Ormåsen is a small residential village in Øvre Eiker municipality in Buskerud county, Norway.
  • C. Jordal
    Jordal is a neighborhood in Oslo, Norway, known for its sports facilities and ice hockey heritage.
  • D. Bekkestua
    Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
  • E. Skutvik
    Skutvik is a small coastal village in Hamarøy Municipality in Nordland county, Norway, known as a ferry port linking the mainland with the Lofoten Islands.
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e7c0e48190af2d68a71130585c completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b591f3c81909ea8a9217d96e0d2 completed May 8, 2026, 11:01 p.m.
NEDg Description generation batch_69fe6c55d6b88190b0f57009be962194 completed May 8, 2026, 11:05 p.m.
NED2 Entity disambiguation (via description) batch_69fe6e56e7e88190b70497e168d707de completed May 8, 2026, 11:14 p.m.
Created at: April 10, 2026, 1:56 a.m.