Triple

T1845932
Position Surface form Disambiguated ID Type / Status
Subject Ostrobothnia E41282 entity
Predicate hasMunicipality P847 FINISHED
Object Nykarleby
Nykarleby is a small bilingual coastal town and municipality in western Finland known for its Swedish-speaking majority and location in the Ostrobothnia region.
 E215151 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: Nykarleby | Statement: [Ostrobothnia, hasMunicipality, Nykarleby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nykarleby
Context triple: [Ostrobothnia, hasMunicipality, Nykarleby]
  • A. Notodden
    Notodden is a town and municipality in Vestfold og Telemark county, Norway, known for its industrial heritage and annual blues festival.
  • B. Malmøya
    Malmøya is a notable island in the Oslofjord known for its natural landscapes and recreational areas near Oslo, Norway.
  • C. Bolnes
    Bolnes is a Dutch surname most notably associated with Catharina Bolnes, the wife of painter Johannes Vermeer.
  • D. Dragsvik
    Dragsvik is a Finnish military locality known for hosting a key coastal garrison of the Finnish Navy.
  • E. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • 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: Nykarleby
Triple: [Ostrobothnia, hasMunicipality, Nykarleby]
Generated description
Nykarleby is a small bilingual coastal town and municipality in western Finland known for its Swedish-speaking majority and location in the Ostrobothnia region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nykarleby
Target entity description: Nykarleby is a small bilingual coastal town and municipality in western Finland known for its Swedish-speaking majority and location in the Ostrobothnia region.
  • A. Notodden
    Notodden is a town and municipality in Vestfold og Telemark county, Norway, known for its industrial heritage and annual blues festival.
  • B. Malmøya
    Malmøya is a notable island in the Oslofjord known for its natural landscapes and recreational areas near Oslo, Norway.
  • C. Bolnes
    Bolnes is a Dutch surname most notably associated with Catharina Bolnes, the wife of painter Johannes Vermeer.
  • D. Dragsvik
    Dragsvik is a Finnish military locality known for hosting a key coastal garrison of the Finnish Navy.
  • E. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • 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_69a88648cd44819093303206d96d76ad completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb051640c819088a8b28a03f57331 completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3c5acb88190aef46483b3318431 completed March 8, 2026, 10:10 p.m.
NEDg Description generation batch_69adf4a146988190aac81580839b1bd5 completed March 8, 2026, 10:13 p.m.
NED2 Entity disambiguation (via description) batch_69adf4f7c908819089ccdc881af10da9 completed March 8, 2026, 10:15 p.m.
Created at: March 4, 2026, 7:33 p.m.