Triple
T7624530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erft River |
E172592
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Kerpen |
E153193
|
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: Kerpen | Statement: [Erft River, flowsThrough, Kerpen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kerpen Context triple: [Erft River, flowsThrough, Kerpen]
-
A.
Kerpen
chosen
Kerpen is a town in North Rhine-Westphalia, Germany, known as the birthplace of Formula 1 champion Michael Schumacher and for its proximity to Cologne.
-
B.
Mechernich
Mechernich is a small town in the Eifel region of North Rhine-Westphalia, Germany, known for its rural landscape and cultural landmarks such as the Bruder Klaus Field Chapel.
-
C.
Neunkirchen
Neunkirchen is a town in southwestern Germany known as one of the major urban centers and former industrial hubs of the state of Saarland.
-
D.
Bottendorf
Bottendorf is a locality in the German state of Thuringia that historically existed within the German Empire.
-
E.
Küdinghoven
Küdinghoven is a district of the Beuel borough in Bonn, Germany, known for its residential character and proximity to 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_69c699517e348190bd3348b6889200f2 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa6648608190a9203b98b76209aa |
completed | March 27, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c870a00f8c8190935ee9b3054ada90 |
completed | March 29, 2026, 12:21 a.m. |
Created at: March 27, 2026, 3:56 p.m.