Triple
T9456266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Langeland |
E228021
|
entity |
| Predicate | connectedTo |
P37
|
FINISHED |
| Object | Tåsinge |
E675341
|
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: Tåsinge | Statement: [Langeland, connectedTo, Tåsinge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tåsinge Context triple: [Langeland, connectedTo, Tåsinge]
-
A.
Tåsinge
chosen
Tåsinge is a Danish island in the South Funen Archipelago known for its picturesque villages, coastal landscapes, and historic manor houses.
-
B.
Abildsø
Abildsø is a residential neighborhood in the borough of Østensjø in Oslo, Norway, known for its green areas and proximity to the lake Østensjøvannet.
-
C.
Vækerø
Vækerø is a residential and commercial area in Oslo, Norway, located along the western waterfront and known for its mix of housing, offices, and green spaces.
-
D.
Norderhov
Norderhov is a village in the municipality of Ringerike in Buskerud, Norway, known for its historic church and rural surroundings.
-
E.
Rudkøbing
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.
- 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_69d122849fec81908a8e7363d6bab4ed |
completed | April 4, 2026, 2:39 p.m. |
Created at: March 30, 2026, 7:52 p.m.