Triple

T3618149
Position Surface form Disambiguated ID Type / Status
Subject Kirkkonummi E76653 entity
Predicate hasNameInFinnish P23453 FINISHED
Object Kirkkonummi E321412 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: Kirkkonummi | Statement: [Kirkkonummi, hasNameInFinnish, Kirkkonummi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kirkkonummi
Context triple: [Kirkkonummi, hasNameInFinnish, Kirkkonummi]
  • A. Kirkkonummi chosen
    Kirkkonummi is a municipality in southern Finland, located just west of Helsinki on the coast of the Gulf of Finland.
  • B. Vantaa
    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.
  • C. Uusikaupunki
    Uusikaupunki is a coastal town and municipality in southwestern Finland known for its maritime heritage and automotive industry.
  • D. Pirkkala
    Pirkkala is a municipality in the Pirkanmaa region of southern Finland, located near the city of Tampere and known for its growing residential areas and proximity to Tampere-Pirkkala Airport.
  • 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 (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_69ad85dae2fc81908d1ceadbc6af0089 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc27dd030819083d34fee0c06612a completed March 8, 2026, 6:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b65082ca248190bfe7350ccc6b6b6a completed March 15, 2026, 6:24 a.m.
Created at: March 8, 2026, 3:23 p.m.