Triple
T10095850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Møn |
E215862
|
entity |
| Predicate | hasMainTown |
P14082
|
FINISHED |
| Object | Stege |
E841319
|
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: Stege | Statement: [Møn, hasMainTown, Stege]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stege Context triple: [Møn, hasMainTown, Stege]
-
A.
Stege
chosen
Stege is the main town on the Danish island of Møn, known for its historic center and coastal setting.
-
B.
Stegen
Stegen is a small village in Bavaria, Germany, situated on the shores of the Ammersee and known for its lakeside recreation and boating.
-
C.
Stiege
Stiege is a small village in the Harz region of Saxony-Anhalt, Germany, now part of the town of Oberharz am Brocken.
-
D.
Steng
Steng is the family name of Austrian actor and director Klaus Maria Brandauer, known for his acclaimed performances in European cinema and Hollywood films.
-
E.
Burgstaaken
Burgstaaken is a small harbour district and marina area on the island of Fehmarn in northern Germany, known for its fishing, tourism, and maritime activities.
- 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_69ca83a4947c8190823a7495dc5d96ed |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd0798c248190af675e30e280daa8 |
completed | April 2, 2026, 2:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2cbeef9a08190a2267f6c7de81170 |
completed | April 5, 2026, 8:54 p.m. |
Created at: March 30, 2026, 9:02 p.m.