Triple

T3441743
Position Surface form Disambiguated ID Type / Status
Subject Dalarna E72579 entity
Predicate contains P35 FINISHED
Object Borlänge E336559 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: Borlänge | Statement: [Dalarna, contains, Borlänge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Borlänge
Context triple: [Dalarna, contains, Borlänge]
  • A. Borlänge chosen
    Borlänge is an industrial town in central Sweden’s Dalarna County, known for its steel production, logistics hub, and role as a regional commercial center.
  • 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. Korsnäs
    Korsnäs is a small coastal municipality in western Finland known for its Swedish-speaking majority and traditional Ostrobothnian rural culture.
  • E. Tungelsta
    Tungelsta is a locality in Stockholm County, Sweden, known for its residential character and commuter connections within the Haninge area.
  • 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_69ad85af50288190a854b76653deee6f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adba276b708190949f294a8d09ec7b completed March 8, 2026, 6:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3548598088190907e13c88cb975fc completed March 13, 2026, 12:04 a.m.
Created at: March 8, 2026, 3:16 p.m.