Triple

T2453237
Position Surface form Disambiguated ID Type / Status
Subject Ainola E53754 entity
Predicate locatedIn P40 FINISHED
Object Järvenpää E53754 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: Järvenpää | Statement: [Ainola, locatedIn, Järvenpää]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Järvenpää
Context triple: [Ainola, locatedIn, Järvenpää]
  • A. Järvenpää chosen
    Järvenpää is a small city in southern Finland known for its lakeside setting and cultural heritage, including its association with composer Jean Sibelius.
  • B. Nurmijärvi
    Nurmijärvi is a municipality in southern Finland known for being one of the largest rural municipalities in the country and part of the Greater Helsinki region.
  • C. Ruovesi
    Ruovesi is a municipality in the Pirkanmaa region of Finland, known for its lakeside landscapes that have inspired Finnish artists and writers.
  • D. Imatra
    Imatra is a town and municipality in southeastern Finland known for its industrial history, proximity to the Russian border, and the Imatrankoski rapids.
  • E. Kerava
    Kerava is a small city in southern Finland known as a commuter town within the Greater Helsinki region.
  • 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_69ab495d227c8190b26ae6548eeb1019 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd0f699308190910a41520dc9efdb completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69b319875d7c8190a43b3efd7d1e54c8 completed March 12, 2026, 7:52 p.m.
Created at: March 6, 2026, 9:43 p.m.