Triple
T10042295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Åboland Swedish |
E205323
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Åboland |
E210759
|
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: Åboland | Statement: [Åboland Swedish, region, Åboland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Åboland Context triple: [Åboland Swedish, region, Åboland]
-
A.
Åboland
chosen
Åboland is a Swedish-speaking coastal and archipelago region in southwestern Finland known for its strong cultural and linguistic ties to the Swedish minority.
-
B.
Ölandet
Ölandet is one of the islands in the Pellinge archipelago off the southern coast of Finland, known for its coastal nature and traditional island scenery.
-
C.
Vestland
Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
-
D.
Zealand
Zealand is the largest and most populous island of Denmark, home to the capital city Copenhagen and a central hub of the country’s cultural and economic life.
-
E.
Schwedeninsel
Schwedeninsel is a small, wooded island located in the Bavarian lake Ammersee in southern Germany.
- 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_69ca834f70e88190b2d74828b7767ec1 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcee48d8c8190af7c93b60f8ca7cb |
completed | April 2, 2026, 2:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d29a35fbc081908ec7d359ec3332f2 |
completed | April 5, 2026, 5:21 p.m. |
Created at: March 30, 2026, 8:55 p.m.