Triple

T14377400
Position Surface form Disambiguated ID Type / Status
Subject Mora E356509 entity
Predicate locatedIn P40 FINISHED
Object Dalarna region E72579 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: Dalarna region | Statement: [Mora, locatedIn, Dalarna region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dalarna region
Context triple: [Mora, locatedIn, Dalarna region]
  • A. Dalarna chosen
    Dalarna is a historical province in central Sweden known for its distinct cultural traditions, including unique dialects, folk costumes, and the iconic Dala horse.
  • B. Jämtland region
    Jämtland region is a sparsely populated county in central Sweden known for its lakes, forests, mountains, and outdoor recreation tourism.
  • C. Dalarna County
    Dalarna County is a central Swedish county known for its traditional culture, red-painted cottages, and iconic Dala horse symbol.
  • D. Dalsland
    Dalsland is a historical province in western Sweden known for its forests, lakes, and rural landscapes.
  • E. Ångermanland
    Ångermanland is a historical province in northern Sweden known for its deep river valleys, forested landscapes, and coastal areas along the Gulf of Bothnia.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de900a67e08190ab1dcf36e6bb3405 completed April 14, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf06f22148190a750a012397b2c68 completed May 8, 2026, 2:17 p.m.
Created at: April 10, 2026, 1:16 a.m.