Triple

T12000114
Position Surface form Disambiguated ID Type / Status
Subject Västernorrland County E285635 entity
Predicate containsSettlement P847 FINISHED
Object Ånge E675671 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: Ånge | Statement: [Västernorrland County, containsSettlement, Ånge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ånge
Context triple: [Västernorrland County, containsSettlement, Ånge]
  • A. Ängelholm
    Ängelholm is a coastal town in southern Sweden known for its sandy beaches, aviation museum, and scenic location at the mouth of the Rönne River.
  • B. Trollhättan
    Trollhättan is a city in western Sweden known for its historic role in the automotive industry and as the longtime home of Saab Automobile’s main production facilities.
  • C. Skellefteå
    Skellefteå is a city in northern Sweden known for its growing high-tech and green industry sector, particularly in battery manufacturing, as well as its ice hockey tradition.
  • D. Sundsvall
    Sundsvall is a coastal city in central Sweden known as an important industrial and commercial center on the Gulf of Bothnia.
  • E. Ånge Municipality chosen
    Ånge Municipality is a local government area in Västernorrland County in northern Sweden, known for its forests, rivers, and position along key rail and road routes.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903c26d7881909b67a31d04882eb5 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f4729eb4a081909d93b3fc74509d86 completed May 1, 2026, 9:30 a.m.
Created at: April 8, 2026, 9:46 p.m.