Triple
T12600281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bergisches Land |
E300838
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Hückeswagen
Hückeswagen is a small historic town in western Germany’s North Rhine-Westphalia, known for its medieval castle and location in the hilly Bergisches Land region.
|
E1071821
|
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: Hückeswagen | Statement: [Bergisches Land, contains, Hückeswagen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hückeswagen Context triple: [Bergisches Land, contains, Hückeswagen]
-
A.
Wilhelmsruh
Wilhelmsruh is a locality in the borough of Pankow in Berlin, Germany, known for its residential character and historical ties to Berlin’s former border zone.
-
B.
Hersbruck
Hersbruck is a small historic town in the Franconian region of Bavaria, Germany, known for its picturesque setting in the Pegnitz Valley and traditional Bavarian architecture.
-
C.
Griesheim
Griesheim is a town in the German state of Hesse, located near the city of Darmstadt and known for its residential character and local industry.
-
D.
Höchheim
Höchheim is a small municipality in the Rhön-Grabfeld district of northern Bavaria, Germany.
-
E.
Wuhletal
Wuhletal is a valley landscape in Berlin shaped by the course of the Wuhle river, featuring green spaces, walking paths, and recreational areas.
- 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: Hückeswagen Triple: [Bergisches Land, contains, Hückeswagen]
Generated description
Hückeswagen is a small historic town in western Germany’s North Rhine-Westphalia, known for its medieval castle and location in the hilly Bergisches Land region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hückeswagen Target entity description: Hückeswagen is a small historic town in western Germany’s North Rhine-Westphalia, known for its medieval castle and location in the hilly Bergisches Land region.
-
A.
Wilhelmsruh
Wilhelmsruh is a locality in the borough of Pankow in Berlin, Germany, known for its residential character and historical ties to Berlin’s former border zone.
-
B.
Hersbruck
Hersbruck is a small historic town in the Franconian region of Bavaria, Germany, known for its picturesque setting in the Pegnitz Valley and traditional Bavarian architecture.
-
C.
Griesheim
Griesheim is a town in the German state of Hesse, located near the city of Darmstadt and known for its residential character and local industry.
-
D.
Höchheim
Höchheim is a small municipality in the Rhön-Grabfeld district of northern Bavaria, Germany.
-
E.
Wuhletal
Wuhletal is a valley landscape in Berlin shaped by the course of the Wuhle river, featuring green spaces, walking paths, and recreational areas.
- 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954d1f6ac8190ab21ca7bcbc80129 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1ad4cc48190a680652efa3ab463 |
completed | May 6, 2026, 8:16 p.m. |
| NEDg | Description generation | batch_69fba5918348819084fa4235eec6eee0 |
completed | May 6, 2026, 8:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fba6b5e4f4819088e8a0629e17e4cc |
completed | May 6, 2026, 8:38 p.m. |
Created at: April 9, 2026, 5:09 p.m.