Triple
T6630354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cologne Bonn metropolitan region |
E149906
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Hürth |
E691066
|
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: Hürth | Statement: [Cologne Bonn metropolitan region, containsCity, Hürth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hürth Context triple: [Cologne Bonn metropolitan region, containsCity, Hürth]
-
A.
Hürth
chosen
Hürth is a town in North Rhine-Westphalia, Germany, best known internationally as the birthplace of Formula One legend Michael Schumacher.
-
B.
Hennef
Hennef is a town in North Rhine-Westphalia, Germany, situated on the river Sieg near Bonn and known for its mix of residential areas, industry, and surrounding countryside.
-
C.
Remscheid
Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
-
D.
Solingen
Solingen is a city in western Germany renowned for its centuries-old blade-making tradition and production of high-quality knives and swords.
-
E.
Radevormwald
Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
- 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_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6afa5c9b48190b645be96d446d0ca |
completed | March 27, 2026, 4:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c98f54f0908190afec4f26e96d8173 |
completed | March 29, 2026, 8:45 p.m. |
Created at: March 27, 2026, 1:59 p.m.