Triple
T10629754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Möhnesee |
E250420
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Hewingsen
Hewingsen is a small village in North Rhine-Westphalia, Germany, that forms part of the municipality of Möhnesee.
|
E875128
|
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: Hewingsen | Statement: [Möhnesee, hasPart, Hewingsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hewingsen Context triple: [Möhnesee, hasPart, Hewingsen]
-
A.
Hodenhagen
Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
-
B.
Knudshoved
Knudshoved is a coastal area on the Danish island of Funen that serves as a key transport hub and former ferry terminal at the western end of the Great Belt crossing.
-
C.
Helenelund
Helenelund is a district and commuter rail station area in Sollentuna, north of central Stockholm, Sweden.
-
D.
Birkholm
Birkholm is a small, sparsely populated Danish island known for its tranquil natural environment and traditional village atmosphere in the South Funen Archipelago.
-
E.
Kessingland
Kessingland is a coastal village and civil parish in Suffolk, England, known for its long shingle beach and seaside tourism.
- 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: Hewingsen Triple: [Möhnesee, hasPart, Hewingsen]
Generated description
Hewingsen is a small village in North Rhine-Westphalia, Germany, that forms part of the municipality of Möhnesee.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hewingsen Target entity description: Hewingsen is a small village in North Rhine-Westphalia, Germany, that forms part of the municipality of Möhnesee.
-
A.
Hodenhagen
Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
-
B.
Knudshoved
Knudshoved is a coastal area on the Danish island of Funen that serves as a key transport hub and former ferry terminal at the western end of the Great Belt crossing.
-
C.
Helenelund
Helenelund is a district and commuter rail station area in Sollentuna, north of central Stockholm, Sweden.
-
D.
Birkholm
Birkholm is a small, sparsely populated Danish island known for its tranquil natural environment and traditional village atmosphere in the South Funen Archipelago.
-
E.
Kessingland
Kessingland is a coastal village and civil parish in Suffolk, England, known for its long shingle beach and seaside tourism.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df92f8388190a8bcff96809d8eb4 |
completed | April 8, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96babc290819096c0c914d038ba01 |
completed | April 10, 2026, 9:29 p.m. |
| NEDg | Description generation | batch_69d96df03c2881909af8501ecf6ac180 |
completed | April 10, 2026, 9:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d96f063d588190adcfd56b2b0afccf |
completed | April 10, 2026, 9:43 p.m. |
Created at: April 8, 2026, 9 p.m.