Triple
T5748246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dueodde |
E126784
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object | Snogebæk |
E138842
|
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: Snogebæk | Statement: [Dueodde, hasNearbySettlement, Snogebæk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snogebæk Context triple: [Dueodde, hasNearbySettlement, Snogebæk]
-
A.
Snogebæk
chosen
Snogebæk is a small coastal village and fishing hamlet on the Danish island of Bornholm, known for its harbor, beaches, and holiday atmosphere.
-
B.
Gryllefjord
Gryllefjord is a small coastal fishing village located on the island of Senja in northern Norway.
-
C.
Nesset
Nesset is a former municipality in western Norway known for its scenic fjord landscapes and rural communities.
-
D.
Sigerfjord
Sigerfjord is a small coastal village in northern Norway, situated on the island of Hinnøya in the Vesterålen region.
-
E.
Strømsø
Strømsø is a historic district and former separate town that now forms part of the city of Drammen in Norway.
- 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_69c00832aedc81909899801b141fa3b4 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02887496c8190b1b9c8dda0d561ef |
completed | March 22, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c097fcba40819097543d151b890788 |
completed | March 23, 2026, 1:31 a.m. |
Created at: March 22, 2026, 3:48 p.m.