Triple

T2301426
Position Surface form Disambiguated ID Type / Status
Subject Tanum E51740 entity
Predicate locatedIn P40 FINISHED
Object Bohuslän E163444 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: Bohuslän | Statement: [Tanum, locatedIn, Bohuslän]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bohuslän
Context triple: [Tanum, locatedIn, Bohuslän]
  • A. Bohuslän chosen
    Bohuslän is a coastal province in western Sweden known for its rugged granite shoreline, fishing villages, and archipelago along the Skagerrak.
  • B. Småland
    Småland is a historical province in southern Sweden known for its forests, lakes, traditional red cottages, and as the birthplace of IKEA founder Ingvar Kamprad.
  • C. Uppland
    Uppland is a historical province in east-central Sweden that includes parts of the greater Stockholm area and key infrastructure such as Stockholm Arlanda Airport.
  • D. Blekinge
    Blekinge is a historical province in southern Sweden on the Baltic Sea coast, known for its archipelago, maritime heritage, and strategic location.
  • E. Dalarna
    Dalarna is a historical province in central Sweden known for its distinct cultural traditions, including unique dialects, folk costumes, and the iconic Dala horse.
  • 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_69a88b0a9f248190bcff941463d8f65a completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc5ef51948190ae828d8ee02feb75 completed March 7, 2026, 6:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef08a105081908455f482c6b2a880 completed March 9, 2026, 4:08 p.m.
Created at: March 4, 2026, 7:49 p.m.