Triple

T5441853
Position Surface form Disambiguated ID Type / Status
Subject Finnish railway network E122151 entity
Predicate borderCrossing P4105 FINISHED
Object Vainikkala E447406 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: Vainikkala | Statement: [Finnish railway network, borderCrossing, Vainikkala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vainikkala
Context triple: [Finnish railway network, borderCrossing, Vainikkala]
  • A. Vainikkala chosen
    Vainikkala is a small Finnish border village and railway station that serves as a key rail crossing point between Finland and Russia on the route between Helsinki and Saint Petersburg.
  • B. Vaajakoski
    Vaajakoski is a district of the city of Jyväskylä in Central Finland, known for its lakeside setting and industrial history.
  • C. Rantasalmi
    Rantasalmi is a rural municipality in the Southern Savonia region of eastern Finland, known for its lakeside landscapes and traditional Finnish countryside.
  • D. Leppävaara
    Leppävaara is a major urban district and transport hub in Espoo, Finland, known for its large shopping center Sello and extensive rail and bus connections.
  • E. Taivalkoski
    Taivalkoski is a rural municipality in Northern Ostrobothnia, Finland, known for its forests, lakes, and outdoor recreation opportunities.
  • 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_69bd46400768819092925d461c0b8432 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd91c131648190b5a7f49efacc874a completed March 20, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf412daa408190a46926f28339aeac completed March 22, 2026, 1:09 a.m.
Created at: March 20, 2026, 2:07 p.m.