Triple

T17118476
Position Surface form Disambiguated ID Type / Status
Subject Terminal 1 (Helsinki Airport) E415400 entity
Predicate servesCity P82 FINISHED
Object Vantaa 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: Vantaa | Statement: [Terminal 1 (Helsinki Airport), servesCity, Vantaa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vantaa
Context triple: [Terminal 1 (Helsinki Airport), servesCity, Vantaa]
  • A. Vantaa chosen
    Vantaa is a major city in the Helsinki metropolitan area of southern Finland, known for hosting Helsinki Airport and serving as an important commercial and residential hub.
  • B. 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.
  • C. Heinola
    Heinola is a small Finnish town in the Päijät-Häme region, known for its lakeside scenery and traditional wooden architecture.
  • D. Kirkkonummi
    Kirkkonummi is a municipality in southern Finland, located just west of Helsinki on the coast of the Gulf of Finland.
  • E. Järvenpää
    Järvenpää is a small city in southern Finland known for its lakeside setting and cultural heritage, including its association with composer Jean Sibelius.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3e8086a388190a655a044feccab14 completed April 18, 2026, 8:22 p.m.
Created at: April 10, 2026, 5:35 a.m.