Triple
T8346822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bishopric of Zülpich |
E196060
|
entity |
| Predicate | seeCity |
P3207
|
FINISHED |
| Object |
Zülpich
Zülpich is a historic town in North Rhine-Westphalia, Germany, known for its Roman heritage and medieval fortifications.
|
E733719
|
NE FINISHED |
How this triple was built (4 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: Zülpich | Statement: [Bishopric of Zülpich, seeCity, Zülpich]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zülpich Context triple: [Bishopric of Zülpich, seeCity, Zülpich]
-
A.
Remscheid
Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
-
B.
Bergkamen
Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
-
C.
Gummersbach
Gummersbach is a town in North Rhine-Westphalia, Germany, known as a regional center in the Bergisches Land and a location for higher education and industry.
-
D.
Waldbröl
Waldbröl is a small town in North Rhine-Westphalia, Germany, known for its rural setting in the Bergisches Land region.
-
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. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Zülpich Triple: [Bishopric of Zülpich, seeCity, Zülpich]
Generated description
Zülpich is a historic town in North Rhine-Westphalia, Germany, known for its Roman heritage and medieval fortifications.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zülpich Target entity description: Zülpich is a historic town in North Rhine-Westphalia, Germany, known for its Roman heritage and medieval fortifications.
-
A.
Remscheid
Remscheid is a city in North Rhine-Westphalia, Germany, known historically for its metalworking industry and as the birthplace of physicist Wilhelm Röntgen.
-
B.
Bergkamen
Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
-
C.
Gummersbach
Gummersbach is a town in North Rhine-Westphalia, Germany, known as a regional center in the Bergisches Land and a location for higher education and industry.
-
D.
Waldbröl
Waldbröl is a small town in North Rhine-Westphalia, Germany, known for its rural setting in the Bergisches Land region.
-
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. chosen
Provenance (5 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_69ca82edd63c8190b876b8465464c5fa |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb8013d81c81908da48466cffb3939 |
completed | March 31, 2026, 8:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1cfe284081909410e023c44c7472 |
completed | April 2, 2026, 7:38 a.m. |
| NEDg | Description generation | batch_69ce1ea3aaf881909562b65cefb20089 |
completed | April 2, 2026, 7:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce1f8d748c81909b331ed822919447 |
completed | April 2, 2026, 7:49 a.m. |
Created at: March 30, 2026, 5:58 p.m.