Triple

T20668168
Position Surface form Disambiguated ID Type / Status
Subject Ondine Records E507946 entity
Predicate basedIn P40 FINISHED
Object Helsinki NE NERFINISHED

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: [Ondine Records, basedIn, Helsinki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helsinki
Context triple: [Ondine Records, basedIn, 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. Mannila
    Mannila is a Finnish surname borne by individuals such as computer scientist Heikki Mannila.
  • C. Espoo
    Espoo is Finland’s second-largest city, located just west of Helsinki on the southern coast, known for its technology industry, natural landscapes, and role as part of the Helsinki metropolitan area.
  • D. Turku
    Turku is one of Finland’s oldest and historically most important cities, located on the southwest coast and known for its medieval heritage and major Baltic Sea port.
  • E. Tampere
    Tampere is a major industrial and cultural city in southern Finland, historically significant as a key battleground in the Finnish Civil War.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4c059bc81908ea762cd73ea4424 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6b5c4c4608190ae17da4a59e5ae80 completed April 20, 2026, 11:24 p.m.
Created at: April 16, 2026, 11:44 a.m.