Triple
T21321951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandvig Beach |
E525639
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Bornholm |
—
|
NE NERFINISHED |
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: Bornholm | Statement: [Sandvig Beach, locatedIn, Bornholm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bornholm Context triple: [Sandvig Beach, locatedIn, Bornholm]
-
A.
Bornholm
chosen
Bornholm is a Danish island known for its rocky coastline, medieval ruins, and picturesque fishing villages in the Baltic Sea.
-
B.
Lolland
Lolland is a large, predominantly agricultural island in southeastern Denmark known for its flat landscape and sugar beet production.
-
C.
Langeland
Langeland is a Danish island in the South Funen Archipelago, known for its rural landscapes, coastal scenery, and historical villages.
-
D.
Rømø
Rømø is a Danish island in the Wadden Sea known for its expansive sandy beaches, coastal dunes, and popular holiday resorts.
-
E.
Ærø
Ærø is a small Danish island in the Baltic Sea known for its picturesque coastal towns, historic architecture, and popular cycling and sailing routes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51ad810819098c12392c8e55f6c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e77ed2640c8190a81b087e2c49c500 |
completed | April 21, 2026, 1:42 p.m. |
Created at: April 16, 2026, 4:40 p.m.