Triple

T8677434
Position Surface form Disambiguated ID Type / Status
Subject Österbottens landskap E205950 entity
Predicate containsMunicipality P852 FINISHED
Object Korsnäs E221676 NE FINISHED

How this triple was built (2 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: Korsnäs | Statement: [Österbottens landskap, containsMunicipality, Korsnäs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Korsnäs
Context triple: [Österbottens landskap, containsMunicipality, Korsnäs]
  • A. Korsnäs chosen
    Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
  • B. Bollnäs
    Bollnäs is a small Swedish town known for its scenic lakeside setting, traditional wooden architecture, and strong bandy sports culture.
  • C. Bollstanäs
    Bollstanäs is a residential locality in Sweden situated within the suburban area of Upplands Väsby, north of Stockholm.
  • D. Kastlösa
    Kastlösa is a small village on the island of Öland in southeastern Sweden, known for its rural landscape and traditional agricultural surroundings.
  • E. Nusnäs
    Nusnäs is a village in Sweden renowned as a traditional center for crafting the iconic painted wooden Dala horses.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca83529a9c8190b5c075b4f14636ed completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc49f7c2c081909ec93413ceefbb1c completed March 31, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf28748c0c8190a8870650a9b07d7d completed April 3, 2026, 2:39 a.m.
Created at: March 30, 2026, 6:32 p.m.