Triple

T17011473
Position Surface form Disambiguated ID Type / Status
Subject Norra E412709 entity
Predicate headquartersLocation P62 FINISHED
Object Helsinki, Finland 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, Finland | Statement: [Norra, headquartersLocation, Helsinki, Finland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helsinki, Finland
Context triple: [Norra, headquartersLocation, Helsinki, Finland]
  • 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. 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.
  • C. 42 Helsinki
    42 Helsinki is a Finnish campus of the global, tuition-free 42 coding school network, offering peer-to-peer, project-based software engineering education.
  • D. Vantaa, Finland
    Vantaa, Finland is a major city in the Helsinki metropolitan area best known for hosting Helsinki Airport and serving as an important transportation and commercial hub.
  • E. Kluuvi, Helsinki
    Kluuvi, Helsinki is a central district of Finland’s capital city, known as a key commercial and cultural hub that includes major shopping streets, offices, and university buildings.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d47bcb508190a799f0bad6b70245 completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a018c3489848190869bebedcb5c0564 completed May 11, 2026, 7:58 a.m.
Created at: April 10, 2026, 5:33 a.m.