Triple

T7770503
Position Surface form Disambiguated ID Type / Status
Subject Ångerman River E179055 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: [Ångerman River, region, Norrland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norrland
Context triple: [Ångerman 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_69c69f30602c819082ab52cd4af5c592 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c70438ca2481909114b0c434717109 completed March 27, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c97660dc8081908781da7ffd606f35 completed March 29, 2026, 6:58 p.m.
Created at: March 27, 2026, 4:11 p.m.