Triple
T7652885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wuppertal |
E173299
|
entity |
| Predicate | river |
P165
|
FINISHED |
| Object | Wupper |
E364898
|
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: Wupper | Statement: [Wuppertal, river, Wupper]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wupper Context triple: [Wuppertal, river, Wupper]
-
A.
Wupper
chosen
The Wupper is a river in North Rhine-Westphalia, Germany, known for flowing through the industrial city of Wuppertal and its surrounding region.
-
B.
Regnitz
The Regnitz is a river in the German state of Bavaria that flows through cities such as Erlangen and Bamberg before joining the Main River.
-
C.
Schwalm River
The Schwalm River is a waterway in the German state of Hesse that lends its name to the surrounding Schwalm-Eder region.
-
D.
Lippe
Lippe is a historical region in northwestern Germany that once formed a small principality and later a Free State within the German Reich.
-
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 (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_69c6995473348190a4f41d110d619a18 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7018c34a88190be6089a9105bd4b0 |
completed | March 27, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8b4f48de88190b9cf40bfb1a26323 |
completed | March 29, 2026, 5:13 a.m. |
Created at: March 27, 2026, 3:58 p.m.