Triple

T13710691
Position Surface form Disambiguated ID Type / Status
Subject Växjö E328762 entity
Predicate hasBodyOfWater P1778 FINISHED
Object Växjösjön E361238 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: Växjösjön | Statement: [Växjö, hasBodyOfWater, Växjösjön]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Växjösjön
Context triple: [Växjö, hasBodyOfWater, Växjösjön]
  • A. Växjö Lake chosen
    Växjö Lake is a scenic freshwater lake in the city of Växjö in southern Sweden, known for its walking paths, recreation areas, and role in the local urban landscape.
  • B. Munksjön
    Munksjön is a small urban lake situated in central Jönköping in southern Sweden, known for its promenades, recreational areas, and proximity to the city’s downtown.
  • C. Ältasjön
    Ältasjön is a lake in the Stockholm area of Sweden, known for its recreational opportunities and natural surroundings within the Nacka nature reserve.
  • D. Storsjön
    Storsjön is a large lake in central Sweden, famed for its scenic surroundings and the local legend of the lake monster Storsjöodjuret.
  • E. Vättern
    Vättern is Sweden's second-largest lake, renowned for its clear waters and surrounding historic towns and landscapes.
  • 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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dd43949e6c8190ae5e4fa119cde33a completed April 13, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69f79d54a68081908df25edf6d5df362 completed May 3, 2026, 7:09 p.m.
Created at: April 9, 2026, 9:54 p.m.