Triple
T7319004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German Bight |
E168488
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Vlieland |
E405468
|
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: Vlieland | Statement: [German Bight, hasPart, Vlieland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vlieland Context triple: [German Bight, hasPart, Vlieland]
-
A.
Vlieland
chosen
Vlieland is a sparsely populated Dutch Wadden Sea island known for its wide beaches, dunes, and car-free, nature-focused tourism.
-
B.
Ameland
Ameland is a Dutch Wadden Sea island known for its sandy beaches, dunes, and nature reserves, popular as a holiday destination in the northern Netherlands.
-
C.
Texel
Texel is the largest and most populated of the West Frisian Islands off the northwestern coast of the Netherlands, known for its beaches, dunes, and nature reserves.
-
D.
Schouwen-Duiveland island
Schouwen-Duiveland island is a Dutch North Sea island in the province of Zeeland, known for its coastal landscapes, beaches, and role in the Delta Works flood protection system.
-
E.
Veendam
Veendam is a town and municipality in the province of Groningen in the northeastern Netherlands, historically known for peat extraction and later for its industrial development.
- 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_69c68a5251508190ad68df4151cfeb04 |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6ef18b7bc81908a9ee405d684f304 |
completed | March 27, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c845df01dc8190ac219c0bb87bd83c |
completed | March 28, 2026, 9:19 p.m. |
Created at: March 27, 2026, 3:02 p.m.