Triple
T7181923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gelsenkirchen |
E167466
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object | Gelsenkirchen-Nord |
E167466
|
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: Gelsenkirchen-Nord | Statement: [Gelsenkirchen, hasDistrict, Gelsenkirchen-Nord]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gelsenkirchen-Nord Context triple: [Gelsenkirchen, hasDistrict, Gelsenkirchen-Nord]
-
A.
Erkrath
Erkrath is a town in the German state of North Rhine-Westphalia, situated near Düsseldorf in the district of Mettmann.
-
B.
Gelsenkirchen
chosen
Gelsenkirchen is a city in western Germany known for its strong football culture and modern stadium, Veltins-Arena, home to FC Schalke 04.
-
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.
Bergkamen
Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
-
E.
Troisdorf
Troisdorf is a town in North Rhine-Westphalia, Germany, located between Cologne and Bonn and known as an important industrial and commuter hub in the Rhine-Sieg district.
- 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_69c6888a7c548190a3d39b52a393080f |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e8bc25088190a7d7f3ba2461b5e9 |
completed | March 27, 2026, 8:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7bf8d76ac8190a2e29f2650e7af28 |
completed | March 28, 2026, 11:46 a.m. |
Created at: March 27, 2026, 2:49 p.m.