Triple

T3486816
Position Surface form Disambiguated ID Type / Status
Subject Växjö E73625 entity
Predicate hasTwinTown P919 FINISHED
Object Kuopio 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 | Statement: [Växjö, hasTwinTown, Kuopio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kuopio
Context triple: [Växjö, hasTwinTown, Kuopio]
  • 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. Kokkola
    Kokkola is a coastal city in western Finland known for its maritime heritage and role as a military and naval hub.
  • C. Oulu
    Oulu is a major city in northern Finland known for its technology industry, university, and position near the Gulf of Bothnia.
  • D. Joensuu
    Joensuu is a city in eastern Finland that serves as a regional center for North Karelia, known for its university, forestry industry, and proximity to lakes and forests.
  • E. Lahti
    Lahti is a city in southern Finland known for its winter sports facilities, particularly ski jumping and cross-country skiing, and for hosting numerous international sporting events.
  • 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_69ad85cca8d4819088494e9f3340fab5 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbb9059f881908f9cbe544365c8df completed March 8, 2026, 6:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5f59074e881908d346937da0b056e completed March 14, 2026, 11:56 p.m.
Created at: March 8, 2026, 3:18 p.m.