Triple

T2950551
Position Surface form Disambiguated ID Type / Status
Subject Central Swedish dialects E79809 entity
Predicate usedIn P98 FINISHED
Object Västmanland E248581 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: Västmanland | Statement: [Central Swedish dialects, usedIn, Västmanland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Västmanland
Context triple: [Central Swedish dialects, usedIn, Västmanland]
  • A. Västmanland chosen
    Västmanland is a historic province in central Sweden known for its forests, lakes, and long tradition of mining and metallurgy.
  • B. Västmanland County
    Västmanland County is an administrative region in central Sweden known for its mix of industrial towns, forests, and lakes.
  • C. Södermanland County
    Södermanland County is an administrative region in east-central Sweden known for its mix of coastal landscapes, forests, and historic towns such as Nyköping and Eskilstuna.
  • D. Västernorrland County
    Västernorrland County is a coastal county in northern Sweden known for its forests, rivers, and towns such as Sundsvall and Härnösand.
  • E. Östergötland County
    Östergötland County is an administrative region in southeastern Sweden known for its mix of historic cities, fertile plains, and coastal and archipelago landscapes along the Baltic Sea.
  • 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_69ad8b1276588190a374a0b12e0f7bdf completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad98fbb7d4819081c241f3ff9165e5 completed March 8, 2026, 3:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b24b079a808190adcbac948ad067e9 completed March 12, 2026, 5:11 a.m.
Created at: March 8, 2026, 2:57 p.m.