Triple

T3441553
Position Surface form Disambiguated ID Type / Status
Subject Gutnish E72575 entity
Predicate region P40 FINISHED
Object Gotland County E121438 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: Gotland County | Statement: [Gutnish, region, Gotland County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gotland County
Context triple: [Gutnish, region, Gotland County]
  • A. Gotland County chosen
    Gotland County is an administrative region of Sweden encompassing the island of Gotland in the Baltic Sea, known for its medieval heritage and unique insular culture.
  • B. Skaraborg County
    Skaraborg County was a former county in Sweden that existed until 1997, when it was merged into the larger Västra Götaland County.
  • C. 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.
  • D. Västerbotten County
    Västerbotten County is a large administrative region in northern Sweden known for its vast forests, coastline along the Gulf of Bothnia, and sparsely populated inland areas.
  • E. Norrbotten County
    Norrbotten County is Sweden’s northernmost and largest county, known for its Arctic climate, vast wilderness, and sparsely populated landscapes.
  • 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_69b373a531348190951041705eebba3d completed March 13, 2026, 2:17 a.m.
Created at: March 8, 2026, 3:16 p.m.