Triple
T1854374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uusimaa |
E41667
|
entity |
| Predicate | hasCoOfficialName |
P20733
|
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: [Uusimaa, hasCoOfficialName, Nyland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nyland Context triple: [Uusimaa, hasCoOfficialName, Nyland]
-
A.
Nyland
chosen
Nyland is the historical Swedish name for the coastal region of southern Finland now known as Uusimaa.
-
B.
Vestland
Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
-
C.
Troms
Troms was a former county in northern Norway known for its Arctic landscapes, coastal fjords, and the city of Tromsø.
-
D.
Solbo
Solbo is a locality within Botkyrka Municipality in Stockholm County, Sweden.
-
E.
Svaneke
Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
- 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_69a8864a83848190a4ec02721306c511 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb07d48c48190bcd34d6093ff5e78 |
completed | March 7, 2026, 4:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeaddc9188190bd49d6605fd0e812 |
completed | March 8, 2026, 9:32 p.m. |
Created at: March 4, 2026, 7:33 p.m.