Triple
T4402900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pernå |
E93657
|
entity |
| Predicate | countrySubdivision |
P766
|
FINISHED |
| Object | Nyland |
E209603
|
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: Nyland | Statement: [Pernå, countrySubdivision, Nyland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nyland Context triple: [Pernå, countrySubdivision, Nyland]
-
A.
Nyland
chosen
Nyland is the historical Swedish name for the coastal region of southern Finland now known as Uusimaa.
-
B.
Mykland
Mykland is a small village in Agder county, Norway, known for its rural setting and surrounding forests and lakes.
-
C.
Eiderstedt
Eiderstedt is a low-lying peninsula on Germany’s North Sea coast known for its dike-protected marshlands, agriculture, and coastal tourism.
-
D.
Helgeland
Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
-
E.
Iveland
Iveland is a small rural municipality in southern Norway known for its forests, agriculture, and mineral resources.
- 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_69b345158c748190a2c040fce2da9980 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b352d08a0c8190ac6c125df40eca75 |
completed | March 12, 2026, 11:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5f5fc9f508190a31adb0758555dfa |
completed | March 14, 2026, 11:57 p.m. |
Created at: March 12, 2026, 11:28 p.m.