Triple

T6696384
Position Surface form Disambiguated ID Type / Status
Subject Southern Sami language E152760 entity
Predicate region P40 FINISHED
Object Härjedalen E356507 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: Härjedalen | Statement: [Southern Sami language, region, Härjedalen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Härjedalen
Context triple: [Southern Sami language, region, Härjedalen]
  • A. Härjedalen chosen
    Härjedalen is a sparsely populated historical province in central Sweden known for its mountainous landscapes, wilderness areas, and outdoor recreation.
  • B. Dalsland
    Dalsland is a historical province in western Sweden known for its forests, lakes, and rural landscapes.
  • C. Jämtland region
    Jämtland region is a sparsely populated county in central Sweden known for its lakes, forests, mountains, and outdoor recreation tourism.
  • D. Närke
    Närke is a historical province in central Sweden known for its Central Swedish dialects and its location around the city of Örebro.
  • E. Dalarna
    Dalarna is a historical province in central Sweden known for its distinct cultural traditions, including unique dialects, folk costumes, and the iconic Dala horse.
  • 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_69c6880687b08190805278b504d1c92c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6b197ccb48190a540feecb2d9c70b completed March 27, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c70af2ede08190821fd599a3bfc879 completed March 27, 2026, 10:55 p.m.
Created at: March 27, 2026, 2:05 p.m.