Triple

T3894939
Position Surface form Disambiguated ID Type / Status
Subject Åre E88146 entity
Predicate locatedIn P40 FINISHED
Object Åre Municipality E88146 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: Åre Municipality | Statement: [Åre, locatedIn, Åre Municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Åre Municipality
Context triple: [Åre, locatedIn, Åre Municipality]
  • A. Åre chosen
    Åre is a well-known ski resort village in northern Sweden, recognized for its alpine skiing and winter sports tourism.
  • B. Sandviken Municipality
    Sandviken Municipality is a local government area in Gävleborg County, Sweden, known for its industrial heritage and the town of Sandviken, home to the steel company Sandvik.
  • C. Samtredia Municipality
    Samtredia Municipality is an administrative district in western Georgia centered around the town of Samtredia, known as a regional transport hub.
  • D. Nykvarn Municipality
    Nykvarn Municipality is a small municipality in Stockholm County, Sweden, known for its rural character, forests, and lakes west of Stockholm.
  • E. Botkyrka Municipality
    Botkyrka Municipality is a suburban municipality in the southern part of the Stockholm metropolitan area in Sweden, known for its cultural diversity and mix of urban and rural environments.
  • 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_69aed9466d548190939f5217a23ed4ac completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeecd197148190b5b24f7097c6049a completed March 9, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51c99bab88190bd63f5b9b3950001 completed March 14, 2026, 8:30 a.m.
Created at: March 9, 2026, 3:21 p.m.