Triple

T4941867
Position Surface form Disambiguated ID Type / Status
Subject Lilla Alby E110954 entity
Predicate countrySubdivision P766 FINISHED
Object Uppland E110264 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: Uppland | Statement: [Lilla Alby, countrySubdivision, Uppland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uppland
Context triple: [Lilla Alby, countrySubdivision, Uppland]
  • A. Uppland chosen
    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.
  • B. Dalsland
    Dalsland is a historical province in western Sweden known for its forests, lakes, and rural landscapes.
  • C. Bohuslän
    Bohuslän is a coastal province in western Sweden known for its rugged granite shoreline, fishing villages, and archipelago along the Skagerrak.
  • D. Närke
    Närke is a historical province in central Sweden known for its Central Swedish dialects and its location around the city of Örebro.
  • E. 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.
  • 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_69bd4415eee08190bdce70276e56a5b4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd70a5f56481908365d0fe16892bf4 completed March 20, 2026, 4:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69befe46b4d081908597c79135415909 completed March 21, 2026, 8:23 p.m.
Created at: March 20, 2026, 1:31 p.m.