Triple
T15281811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Urho Kekkonen National Park |
E365287
|
entity |
| Predicate | nearestCity |
P350
|
FINISHED |
| Object | Saariselkä |
—
|
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: Saariselkä | Statement: [Urho Kekkonen National Park, nearestCity, Saariselkä]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saariselkä Context triple: [Urho Kekkonen National Park, nearestCity, Saariselkä]
-
A.
Saariselkä
chosen
Saariselkä is a popular holiday resort village in Finnish Lapland, known for its ski slopes, outdoor activities, and access to the surrounding Arctic wilderness.
-
B.
Loviisa
Loviisa is a small coastal town and municipality in southern Finland known for its historic wooden houses, seaside location, and nuclear power plant.
-
C.
Saarijärvi
Saarijärvi is a town and municipality in the Central Finland region, known for its numerous lakes and forested landscapes.
-
D.
Kalajoki
Kalajoki is a coastal town and municipality in Northern Ostrobothnia, Finland, known for its long sandy beaches and tourism.
-
E.
Sotkamo
Sotkamo is a municipality in eastern Finland known for its mining industry, outdoor recreation, and the popular Vuokatti ski and sports resort area.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00e51f82081909f63d14b589d5587 |
completed | April 15, 2026, 10:16 p.m. |
Created at: April 10, 2026, 3:15 a.m.