Triple

T2567976
Position Surface form Disambiguated ID Type / Status
Subject Microsoft Mobile E57595 entity
Predicate headquartersLocation P62 FINISHED
Object Espoo, Finland E58506 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: Espoo, Finland | Statement: [Microsoft Mobile, headquartersLocation, Espoo, Finland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Espoo, Finland
Context triple: [Microsoft Mobile, headquartersLocation, Espoo, Finland]
  • A. Espoo, Finland chosen
    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.
  • B. 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.
  • C. Kirkkonummi, Finland
    Kirkkonummi, Finland is a coastal municipality in southern Finland near Helsinki, known for its natural landscapes and as the birthplace of architect Eero Saarinen.
  • D. Helsinki
    Helsinki is the capital and largest city of Finland, known for its coastal location on the Baltic Sea, modern design, and vibrant cultural life.
  • 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_69ab4a51410081908501dcf8bad9adc4 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd36191848190b6255fa9029429bd completed March 7, 2026, 7:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69af6569e38881908d1492277fe0c60c completed March 10, 2026, 12:27 a.m.
Created at: March 6, 2026, 9:48 p.m.