Triple

T15678235
Position Surface form Disambiguated ID Type / Status
Subject Jyväskylä railway station E377500 entity
Predicate hasConnectionTo P845 FINISHED
Object Pieksämäki E646370 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: Pieksämäki | Statement: [Jyväskylä railway station, hasConnectionTo, Pieksämäki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pieksämäki
Context triple: [Jyväskylä railway station, hasConnectionTo, Pieksämäki]
  • A. Pieksämäki chosen
    Pieksämäki is a town in Southern Savonia, Finland, known as a regional transport hub with significant railway and road connections.
  • B. Kokemäki
    Kokemäki is a small town and municipality in the Satakunta region of western Finland, known for its location along the Kokemäenjoki River and its historical roots dating back to medieval times.
  • C. Luumäki
    Luumäki is a rural municipality in South Karelia, southeastern Finland, known for its forests, lakes, and historical significance.
  • D. Tikkakoski
    Tikkakoski is a district in Jyväskylä, Finland, known for its military air base and role as a key center for the Finnish Air Force.
  • E. Leivonmäki
    Leivonmäki is a former rural municipality in Central Finland known for its forests, lakes, and the Leivonmäki National Park.
  • 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f2f1640819086efd5a73bb9734a completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ee0446881909e9c2504d51d49a3 completed May 9, 2026, 5:29 p.m.
Created at: April 10, 2026, 4:16 a.m.