Triple

T10449556
Position Surface form Disambiguated ID Type / Status
Subject Ume River E246381 entity
Predicate region P40 FINISHED
Object Norrland E82897 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: Norrland | Statement: [Ume River, region, Norrland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norrland
Context triple: [Ume River, region, Norrland]
  • A. 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.
  • B. Jämtland region
    Jämtland region is a sparsely populated county in central Sweden known for its lakes, forests, mountains, and outdoor recreation tourism.
  • C. Götaland
    Götaland is one of Sweden’s three major historical lands, encompassing the country’s southern regions and several of its largest cities.
  • D. northern Sweden chosen
    Northern Sweden is a sparsely populated, subarctic region known for its vast forests, mountains, and traditional Sámi culture, including reindeer herding and indigenous languages.
  • E. Ostrobothnia
    Ostrobothnia is a coastal region in western Finland known for its strong Swedish-speaking population, flat landscapes, and historic maritime and agricultural traditions.
  • 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_69d381c04fe08190957c26c526a3b05a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4fe09af04819083db42f4de4cb0a9 completed April 7, 2026, 12:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69d87efedf6c8190aa4b7bbe5f160eeb completed April 10, 2026, 4:39 a.m.
Created at: April 6, 2026, 12:17 p.m.