Triple
T7591557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Funen Archipelago |
E179746
|
entity |
| Predicate | containsIsland |
P970
|
FINISHED |
| Object | Avernakø |
E675342
|
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: Avernakø | Statement: [South Funen Archipelago, containsIsland, Avernakø]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avernakø Context triple: [South Funen Archipelago, containsIsland, Avernakø]
-
A.
Avernakø
chosen
Avernakø is a small Danish island in the South Funen Archipelago known for its rural landscapes, coastal scenery, and traditional village life.
-
B.
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.
-
C.
Kvænangen
Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
-
D.
Norg
Norg is a village in the Dutch province of Drenthe, known for its historic farms, surrounding forests, and role as a local tourist destination.
-
E.
Rennebu
Rennebu is a rural municipality in Trøndelag county, Norway, known for its distinctive Y-shaped church and scenic valley landscapes.
- 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_69c69f335248819093c1006f30513708 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f9b746ac8190b255afdfb9635f72 |
completed | March 27, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c86843a7808190a4c1d3c33a7441ed |
completed | March 28, 2026, 11:46 p.m. |
Created at: March 27, 2026, 3:53 p.m.