Triple
T17052950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borne |
E413746
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Rheine |
—
|
NE NERFINISHED |
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: Rheine | Statement: [Borne, hasTwinTown, Rheine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rheine Context triple: [Borne, hasTwinTown, Rheine]
-
A.
Rheine
chosen
Rheine is a German city in the state of North Rhine-Westphalia, known for its historical town center and location along the River Ems.
-
B.
Rhein II
Rhein II is a large-scale color photograph by German visual artist Andreas Gursky, renowned for its minimalist depiction of the Rhine River and for once being the most expensive photograph ever sold at auction.
-
C.
Blies
The Blies is a river in western Germany and northeastern France that flows through the Saarland region before joining the Saar River.
-
D.
Roer
The Roer is a river in Western Europe that flows through parts of Belgium, Germany, and the Netherlands before joining the Meuse.
-
E.
Lippe
The Lippe is a river in western Germany that flows through North Rhine-Westphalia and is a right-bank tributary of the Rhine.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3daa491008190ad013ee37532aa51 |
completed | April 18, 2026, 7:25 p.m. |
Created at: April 10, 2026, 5:34 a.m.