Triple
T1037313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kemi |
E22392
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Lapland |
E73789
|
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: Lapland | Statement: [Kemi, locatedIn, Lapland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lapland Context triple: [Kemi, locatedIn, Lapland]
-
A.
Lapland
chosen
Lapland is a sparsely populated Arctic region in northern Finland known for its subarctic wilderness, indigenous Sámi culture, and reputation as the home of Santa Claus.
-
B.
Fennoscandia
Fennoscandia is a geological and geographical region in northern Europe that encompasses the Scandinavian and Kola peninsulas, Finland, and parts of northwestern Russia.
-
C.
Karelia
Karelia is a historical and cultural region of northern Europe, spanning areas of present-day Finland and Russia and known for its distinct Karelian people, language, and forested lake landscapes.
-
D.
Vestland
Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
-
E.
Nord
Nord is a department in northern France known for its industrial heritage, dense population, and proximity to Belgium.
- 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_69a493d848848190aed4011b34b2e8d3 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b82a1014819085bfc077e24c9742 |
completed | March 1, 2026, 10:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3bc378fc8190846d5ffce73371dd |
completed | March 7, 2026, 2:52 p.m. |
Created at: March 1, 2026, 7:41 p.m.