Triple
T15757578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Innerste |
E382006
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object |
Groß Düngen
Groß Düngen is a village in Lower Saxony, Germany, situated near the town of Bad Salzdetfurth in the Hildesheim district.
|
E1177731
|
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: Groß Düngen | Statement: [Innerste, flowsThrough, Groß Düngen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Groß Düngen Context triple: [Innerste, flowsThrough, Groß Düngen]
-
A.
Magdeburg Börde
Magdeburg Börde is a fertile loess plain in central Germany known for its highly productive agricultural land, especially for growing sugar beets and cereals.
-
B.
Schildwolde
Schildwolde is a village in the Dutch province of Groningen, known for its historic church and rural character within the municipality of Midden-Groningen.
-
C.
Wuhlheide
Wuhlheide is a large forested park and recreational area in Berlin known for its green spaces, outdoor activities, and cultural venues.
-
D.
Uckersee
Uckersee is a lake in northeastern Germany’s Uckermark region, known for its natural landscapes and recreational activities such as boating and fishing.
-
E.
Großwiese
Großwiese is a locality or district that forms part of the municipality of Metten in Bavaria, Germany.
- 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: Groß Düngen Triple: [Innerste, flowsThrough, Groß Düngen]
Generated description
Groß Düngen is a village in Lower Saxony, Germany, situated near the town of Bad Salzdetfurth in the Hildesheim district.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Groß Düngen Target entity description: Groß Düngen is a village in Lower Saxony, Germany, situated near the town of Bad Salzdetfurth in the Hildesheim district.
-
A.
Magdeburg Börde
Magdeburg Börde is a fertile loess plain in central Germany known for its highly productive agricultural land, especially for growing sugar beets and cereals.
-
B.
Schildwolde
Schildwolde is a village in the Dutch province of Groningen, known for its historic church and rural character within the municipality of Midden-Groningen.
-
C.
Wuhlheide
Wuhlheide is a large forested park and recreational area in Berlin known for its green spaces, outdoor activities, and cultural venues.
-
D.
Uckersee
Uckersee is a lake in northeastern Germany’s Uckermark region, known for its natural landscapes and recreational activities such as boating and fishing.
-
E.
Großwiese
Großwiese is a locality or district that forms part of the municipality of Metten in Bavaria, Germany.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b1ff4881909d5240d1d30f5c8b |
completed | April 16, 2026, 3 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff9096d65c81908755cae83cc48e61 |
completed | May 9, 2026, 7:52 p.m. |
| NEDg | Description generation | batch_69ff929442748190a8c5df31e6730046 |
completed | May 9, 2026, 8:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff935e5d3881908215b6f45b7b6bf5 |
completed | May 9, 2026, 8:04 p.m. |
Created at: April 10, 2026, 4:47 a.m.