Triple
T9456236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langeland |
E228021
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Rudkøbing |
E286509
|
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: Rudkøbing | Statement: [Langeland, hasSettlement, Rudkøbing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rudkøbing Context triple: [Langeland, hasSettlement, Rudkøbing]
-
A.
Rudkøbing
chosen
Rudkøbing is a small historic town on the Danish island of Langeland, known for its well-preserved old streets and as the birthplace of physicist Hans Christian Ørsted.
-
B.
Sakskøbing
Sakskøbing is a small town on the Danish island of Lolland, known for its historic church, harbor, and surrounding agricultural landscape.
-
C.
Nakskov
Nakskov is a historic port town in southern Denmark located on the island of Lolland, known for its maritime industry and coastal setting.
-
D.
Korsholm
Korsholm is a coastal municipality in western Finland, known for its largely Swedish-speaking population and proximity to the city of Vaasa in the Ostrobothnia region.
-
E.
Vordingborg
Vordingborg is a historic coastal town in southern Denmark known for the ruins of Vordingborg Castle and its prominent Goose Tower.
- 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_69ca843b123881909b0e60028475d12d |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f8f7e1481909318e473ab4d6460 |
completed | April 1, 2026, 8:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d22840c4548190b1610e2c3cec6220 |
completed | April 5, 2026, 9:15 a.m. |
Created at: March 30, 2026, 7:52 p.m.