Triple
T10013951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Frisian Islands |
E199440
|
entity |
| Predicate | hasLargestIsland |
P756
|
FINISHED |
| Object | Sylt |
E231952
|
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: Sylt | Statement: [North Frisian Islands, hasLargestIsland, Sylt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sylt Context triple: [North Frisian Islands, hasLargestIsland, Sylt]
-
A.
Sylt
chosen
Sylt is a popular German North Sea island known for its long sandy beaches, distinctive dune landscapes, and status as an upscale holiday destination.
-
B.
Terschelling
Terschelling is a Dutch Wadden Sea island known for its sandy beaches, dunes, and nature reserves, popular as a holiday destination and part of the UNESCO-listed Wadden Sea region.
-
C.
Gotland
Gotland is Sweden’s largest island, located in the Baltic Sea and known for its medieval town of Visby, limestone cliffs, and rich Viking-era history.
-
D.
Föhr
Föhr is a North Frisian island off the coast of Schleswig-Holstein in northern Germany, known for its mild climate, sandy beaches, and traditional Frisian culture.
-
E.
Rømø
Rømø is a Danish island in the Wadden Sea known for its expansive sandy beaches, coastal dunes, and popular holiday resorts.
- 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_69ca8315a1a08190ab310f25620f362b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cdcd3e35508190920468be167cb708 |
completed | April 2, 2026, 1:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d26a8f6f3081909310e28725d31f7e |
completed | April 5, 2026, 1:58 p.m. |
Created at: March 30, 2026, 8:52 p.m.