Triple
T16065290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dutch Limburg |
E389715
|
entity |
| Predicate | containsRiver |
P165
|
FINISHED |
| Object | Roer |
E180110
|
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: Roer | Statement: [Dutch Limburg, containsRiver, Roer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roer Context triple: [Dutch Limburg, containsRiver, Roer]
-
A.
Roer
chosen
The Roer is a river in Western Europe that flows through parts of Belgium, Germany, and the Netherlands before joining the Meuse.
-
B.
Rheine
Rheine is a German city in the state of North Rhine-Westphalia, known for its historical town center and location along the River Ems.
-
C.
Erft River
The Erft River is a tributary of the Rhine in western Germany, flowing through North Rhine-Westphalia and known for passing historic towns and former mining areas before joining the Rhine near Neuss.
-
D.
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.
-
E.
Rhens
Rhens is a historic town on the Rhine River in western Germany, known for its medieval role as a meeting place of the prince-electors of the Holy Roman Empire.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1837bec688190a77ad347600b6bdc |
completed | April 17, 2026, 12:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a502c82881908d5b6f7c23e8a403 |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 4:57 a.m.