Triple
T10568968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ahrensburg |
E249427
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object |
Bredenbek
Bredenbek is a small river in northern Germany that flows through the town of Ahrensburg in the state of Schleswig-Holstein.
|
E873690
|
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: Bredenbek | Statement: [Ahrensburg, hasRiver, Bredenbek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bredenbek Context triple: [Ahrensburg, hasRiver, Bredenbek]
-
A.
Roderwolde
Roderwolde is a small rural village in the Dutch province of Drenthe, known for its historic church and traditional countryside landscape.
-
B.
Biessum
Biessum is a small village in the province of Groningen in the Netherlands, now part of the municipality of Eemsdelta.
-
C.
Groesbeek
Groesbeek is a village in the Dutch province of Gelderland, known for its hilly landscape, World War II history, and wine production.
-
D.
Betuwe
Betuwe is a fertile riverine region in the Dutch province of Gelderland, renowned for its extensive fruit orchards and scenic landscapes between the Rhine and Waal rivers.
-
E.
Vollenhove
Vollenhove is a historic town in the Dutch province of Overijssel, known for its former status as a regional administrative and noble center with several notable estates and churches.
- 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: Bredenbek Triple: [Ahrensburg, hasRiver, Bredenbek]
Generated description
Bredenbek is a small river in northern Germany that flows through the town of Ahrensburg in the state of Schleswig-Holstein.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bredenbek Target entity description: Bredenbek is a small river in northern Germany that flows through the town of Ahrensburg in the state of Schleswig-Holstein.
-
A.
Roderwolde
Roderwolde is a small rural village in the Dutch province of Drenthe, known for its historic church and traditional countryside landscape.
-
B.
Biessum
Biessum is a small village in the province of Groningen in the Netherlands, now part of the municipality of Eemsdelta.
-
C.
Groesbeek
Groesbeek is a village in the Dutch province of Gelderland, known for its hilly landscape, World War II history, and wine production.
-
D.
Betuwe
Betuwe is a fertile riverine region in the Dutch province of Gelderland, renowned for its extensive fruit orchards and scenic landscapes between the Rhine and Waal rivers.
-
E.
Vollenhove
Vollenhove is a historic town in the Dutch province of Overijssel, known for its former status as a regional administrative and noble center with several notable estates and churches.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5272ff53c8190ae7c399d49b585f5 |
completed | April 7, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95e7396a4819082cc73c736636fb9 |
completed | April 10, 2026, 8:32 p.m. |
| NEDg | Description generation | batch_69d95f80d0c48190b88e3a4b3e42279c |
completed | April 10, 2026, 8:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d9602748608190b0c971accf44b7aa |
completed | April 10, 2026, 8:40 p.m. |
Created at: April 6, 2026, 12:37 p.m.