Triple
T5138363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finnish Lakeland |
E115882
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Joensuu |
E167288
|
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: Joensuu | Statement: [Finnish Lakeland, majorCity, Joensuu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joensuu Context triple: [Finnish Lakeland, majorCity, Joensuu]
-
A.
Joensuu
chosen
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.
-
B.
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.
-
C.
Kokkola
Kokkola is a coastal city in western Finland known for its maritime heritage and role as a military and naval hub.
-
D.
Lappeenranta
Lappeenranta is a city in southeastern Finland near the Russian border, known for its lakeside location on Saimaa and its role as a regional commercial and educational center.
-
E.
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.
- 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd787acd18819087f09db885893c3e |
completed | March 20, 2026, 4:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf77a987ec8190bda4df37468d9918 |
completed | March 22, 2026, 5:01 a.m. |
Created at: March 20, 2026, 1:43 p.m.