Triple

T688272
Position Surface form Disambiguated ID Type / Status
Subject Bursa E13331 entity
Predicate hasSisterCity P919 FINISHED
Object Helsinki E14163 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: Helsinki | Statement: [Bursa, hasSisterCity, Helsinki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helsinki
Context triple: [Bursa, hasSisterCity, Helsinki]
  • A. Helsinki chosen
    Helsinki is the capital and largest city of Finland, known for its coastal location on the Baltic Sea, modern design, and vibrant cultural life.
  • B. Tallinn
    Tallinn is the capital and largest city of Estonia, a historic Baltic Sea port known for its well-preserved medieval Old Town and strategic maritime location.
  • C. Lappeenranta
    Lappeenranta is a city in southeastern Finland near the Russian border, known for its lakeside location on Saimaa and its role as a regional commercial and educational center.
  • D. Jyväskylä
    Jyväskylä is a central Finnish city known for its lakeside setting, strong educational institutions, and association with architect Alvar Aalto.
  • E. Espoo, Finland
    Espoo, Finland is a major city in the Helsinki metropolitan area known as a technology and innovation hub that has long hosted the corporate headquarters of Nokia.
  • 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_69a4933e0f98819097d22766c49b61b8 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a0953fb481909e1d4177ee191351 completed March 1, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a64a53c068819089e66347da55710b completed March 3, 2026, 2:41 a.m.
Created at: March 1, 2026, 7:36 p.m.