Triple

T14895012
Position Surface form Disambiguated ID Type / Status
Subject Österdalälven E359848 entity
Predicate drainsRegion P1559 FINISHED
Object northern Dalarna 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: northern Dalarna | Statement: [Österdalälven, drainsRegion, northern Dalarna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: northern Dalarna
Context triple: [Österdalälven, drainsRegion, northern Dalarna]
  • 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. province of Dalarna
    The province of Dalarna is a historic region in central Sweden known for its traditional folk culture, red-painted cottages, and iconic Dala horse carvings.
  • C. Dalsland
    Dalsland is a historical province in western Sweden known for its forests, lakes, and rural landscapes.
  • D. Jämtland region
    Jämtland region is a sparsely populated county in central Sweden known for its lakes, forests, mountains, and outdoor recreation tourism.
  • E. northern Sweden
    Northern Sweden is a sparsely populated, subarctic region known for its vast forests, mountains, and traditional Sámi culture, including reindeer herding and indigenous languages.
  • 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_69d827980cbc8190a0c569ae3940a1d9 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69ded6070b248190be8f4f91a0c0b1f3 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b679fb081908cf8f41acfba3b99 completed May 8, 2026, 11:01 p.m.
Created at: April 10, 2026, 2:10 a.m.