Triple

T11921222
Position Surface form Disambiguated ID Type / Status
Subject Marl, Germany E283658 entity
Predicate hasTwinTown P919 FINISHED
Object Kuopio, Finland E357411 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: Kuopio, Finland | Statement: [Marl, Germany, hasTwinTown, Kuopio, Finland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kuopio, Finland
Context triple: [Marl, Germany, hasTwinTown, Kuopio, Finland]
  • A. Kuopio chosen
    Kuopio is a city in eastern Finland known for its lakeside setting, vibrant cultural life, and status as a regional center for education and commerce.
  • B. Kirkkonummi, Finland
    Kirkkonummi, Finland is a coastal municipality in southern Finland near Helsinki, known for its natural landscapes and as the birthplace of architect Eero Saarinen.
  • C. Kouvola
    Kouvola is a city in southeastern Finland known as a regional transport hub and gateway to the nearby Repovesi National Park.
  • D. Kerava
    Kerava is a small city in southern Finland known as a commuter town within the Greater Helsinki region.
  • E. Kokkola
    Kokkola is a coastal city in western Finland known for its maritime heritage and role as a military and naval hub.
  • 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_69d6ab2c07e88190ba13b0d21fd6cf33 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e8e1b08481909ed291667035f330 completed April 10, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69f44033c288819099587af3f895eac5 completed May 1, 2026, 5:54 a.m.
Created at: April 8, 2026, 9:45 p.m.