Triple
T6487789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beuel |
E146557
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Küdinghoven
Küdinghoven is a district of the Beuel borough in Bonn, Germany, known for its residential character and proximity to the Rhine.
|
E595683
|
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: Küdinghoven | Statement: [Beuel, hasPart, Küdinghoven]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Küdinghoven Context triple: [Beuel, hasPart, Küdinghoven]
-
A.
Nellingen
Nellingen is a small municipality in the Alb-Donau district of the German state of Baden-Württemberg, situated on the Swabian Jura plateau.
-
B.
Leichlingen
Leichlingen is a small town in North Rhine-Westphalia, Germany, known for its scenic location along the Wupper River and its fruit-growing traditions.
-
C.
Gailingen
Gailingen is a village in the German municipality of Gailingen am Hochrhein in the state of Baden-Württemberg, near the Swiss border along the High Rhine.
-
D.
Illerkirchberg
Illerkirchberg is a small municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm along the Iller River.
-
E.
Nieuwenhoorn
Nieuwenhoorn is a village in the western Netherlands that forms part of the province of South Holland.
- 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: Küdinghoven Triple: [Beuel, hasPart, Küdinghoven]
Generated description
Küdinghoven is a district of the Beuel borough in Bonn, Germany, known for its residential character and proximity to the Rhine.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Küdinghoven Target entity description: Küdinghoven is a district of the Beuel borough in Bonn, Germany, known for its residential character and proximity to the Rhine.
-
A.
Nellingen
Nellingen is a small municipality in the Alb-Donau district of the German state of Baden-Württemberg, situated on the Swabian Jura plateau.
-
B.
Leichlingen
Leichlingen is a small town in North Rhine-Westphalia, Germany, known for its scenic location along the Wupper River and its fruit-growing traditions.
-
C.
Gailingen
Gailingen is a village in the German municipality of Gailingen am Hochrhein in the state of Baden-Württemberg, near the Swiss border along the High Rhine.
-
D.
Illerkirchberg
Illerkirchberg is a small municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm along the Iller River.
-
E.
Nieuwenhoorn
Nieuwenhoorn is a village in the western Netherlands that forms part of the province of South Holland.
- 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_69c0090158c08190af0df9a2348d2d52 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a96a4048190a28dee5fd9258486 |
completed | March 22, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c653b792f48190b301cdc643db8ddf |
completed | March 27, 2026, 9:53 a.m. |
| NEDg | Description generation | batch_69c6545575788190acb374fcdb7f5edf |
completed | March 27, 2026, 9:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c654c0cdf88190994217223fb2f77a |
completed | March 27, 2026, 9:58 a.m. |
Created at: March 22, 2026, 4:52 p.m.