Triple

T1854337
Position Surface form Disambiguated ID Type / Status
Subject Uusimaa E41667 entity
Predicate contains P35 FINISHED
Object Vantaa E172139 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: Vantaa | Statement: [Uusimaa, contains, Vantaa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vantaa
Context triple: [Uusimaa, contains, Vantaa]
  • A. 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.
  • B. Järvenpää
    Järvenpää is a small city in southern Finland known for its lakeside setting and cultural heritage, including its association with composer Jean Sibelius.
  • C. 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.
  • D. Uusikaupunki
    Uusikaupunki is a coastal town and municipality in southwestern Finland known for its maritime heritage and automotive industry.
  • E. Vantaa, Finland chosen
    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.
  • 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_69a8864a83848190a4ec02721306c511 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb06b3f08819092b3fbdff83b3097 completed March 7, 2026, 4:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8645ae0819098d74988de56a7b4 completed March 10, 2026, 9:46 a.m.
Created at: March 4, 2026, 7:33 p.m.