Triple

T478170
Position Surface form Disambiguated ID Type / Status
Subject Nokia E9106 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: [Nokia, headquartersLocation, Espoo, Finland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Espoo, Finland
Context triple: [Nokia, 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. 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.
  • 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. Järvenpää
    Järvenpää is a small city in southern Finland known for its lakeside setting and cultural heritage, including its association with composer Jean Sibelius.
  • E. Hämeenlinna
    Hämeenlinna is a historic city in southern Finland known for its medieval castle, cultural heritage, and role as a regional administrative and educational center.
  • 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_69a2e7ff81708190b0507a24a997232c completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f03f3fbc81909af6e4496d5e6c2a completed Feb. 28, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69a46c5f07808190aeafebb8e7cd7df9 completed March 1, 2026, 4:42 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.