Triple

T20239497
Position Surface form Disambiguated ID Type / Status
Subject Lake Päijänne E498243 entity
Predicate hasCityOnShore P969 FINISHED
Object Jyväskylä 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: Jyväskylä | Statement: [Lake Päijänne, hasCityOnShore, Jyväskylä]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jyväskylä
Context triple: [Lake Päijänne, hasCityOnShore, Jyväskylä]
  • A. Jyväskylä chosen
    Jyväskylä is a central Finnish city known for its lakeside setting, strong educational institutions, and association with architect Alvar Aalto.
  • B. Joensuu
    Joensuu is a city in eastern Finland that serves as a regional center for North Karelia, known for its university, forestry industry, and proximity to lakes and forests.
  • 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. Kouvola
    Kouvola is a city in southeastern Finland known as a regional transport hub and gateway to the nearby Repovesi National Park.
  • E. Kuopio
    Kuopio is a city in eastern Finland known for its lakeside setting, vibrant cultural life, and status as a regional center for education and commerce.
  • 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_69da6274c58c81909c646eabed6f4f30 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6716dd0b081909d4063150cdc0c02 completed April 20, 2026, 6:33 p.m.
Created at: April 11, 2026, 11:40 p.m.