Triple
T10567805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aabenraa |
E249394
|
entity |
| Predicate | locatedEastOf |
P4240
|
FINISHED |
| Object | Tønder |
E635019
|
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: Tønder | Statement: [Aabenraa, locatedEastOf, Tønder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tønder Context triple: [Aabenraa, locatedEastOf, Tønder]
-
A.
Tønder
chosen
Tønder is a historic market town in southern Denmark near the German border, known for its well-preserved old town and cultural heritage.
-
B.
Skjern
Skjern is a town in western Jutland, Denmark, known for its location near the Skjern River and its surrounding agricultural landscape.
-
C.
Vordingborg
Vordingborg is a historic coastal town in southern Denmark known for the ruins of Vordingborg Castle and its prominent Goose Tower.
-
D.
Vejle
Vejle is a Danish city known for its scenic fjord setting, rolling hills, and role as a regional commercial and transportation hub in southeastern Jutland.
-
E.
Næstved
Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5272ef5848190b76d671ea2d26314 |
completed | April 7, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96b5025b88190a078f5ad7b9cb3d5 |
completed | April 10, 2026, 9:27 p.m. |
Created at: April 6, 2026, 12:36 p.m.