Triple
T7652880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wuppertal |
E173299
|
entity |
| Predicate | formedByMergerOf |
P77
|
FINISHED |
| Object | Ronsdorf |
E78956
|
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: Ronsdorf | Statement: [Wuppertal, formedByMergerOf, Ronsdorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ronsdorf Context triple: [Wuppertal, formedByMergerOf, Ronsdorf]
-
A.
Ronsdorf
chosen
Ronsdorf is a district of the German city of Wuppertal in North Rhine-Westphalia, historically known as an independent town in the Bergisches Land region.
-
B.
Rahnsdorf
Rahnsdorf is a lakeside locality in eastern Berlin, Germany, known for its village-like character, forests, and waterfront along the Müggelsee and nearby waterways.
-
C.
Ruppersdorf
Ruppersdorf is a small locality in Germany, historically part of East Prussia, known as the birthplace of German general Otto Lasch.
-
D.
Rüngsdorf
Rüngsdorf is a residential district in the southern part of Bonn, Germany, known for its scenic location along the Rhine and its affiliation with the Bad Godesberg borough.
-
E.
Dierdorf
Dierdorf is a surname most prominently associated with former American football player and sportscaster Dan Dierdorf.
- 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_69c922a94b3881908a3482ca45891df7 |
completed | March 29, 2026, 1:01 p.m. |
Created at: March 27, 2026, 3:58 p.m.