Triple
T13469039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Essen |
E311580
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object | Kettwig |
E1158185
|
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: Kettwig | Statement: [Essen, hasDistrict, Kettwig]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kettwig Context triple: [Essen, hasDistrict, Kettwig]
-
A.
Kettwig
chosen
Kettwig is a historic district of the German city of Essen, known for its picturesque old town along the Ruhr River and scenic lakeside surroundings.
-
B.
Bergkamen
Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
-
C.
Monschau
Monschau is a historic small town in western Germany’s Eifel region, known for its well-preserved half-timbered houses, medieval center, and scenic setting along the Rur River.
-
D.
Wermelskirchen
Wermelskirchen is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Bergisches Land region and its traditional half-timbered architecture.
-
E.
Remscheid
Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf21e46081908a00c9acf54f270f |
completed | April 12, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2ce12e78819080b3fe19c57ef3ef |
completed | May 9, 2026, 12:47 p.m. |
Created at: April 9, 2026, 9:42 p.m.