Triple
T6624491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schweinfurt region |
E149760
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Schwebheim
Schwebheim is a small municipality in northern Bavaria, Germany, known for its rural character and proximity to the city of Schweinfurt.
|
E614094
|
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: Schwebheim | Statement: [Schweinfurt region, containsTown, Schwebheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schwebheim Context triple: [Schweinfurt region, containsTown, Schwebheim]
-
A.
Marlenheim
Marlenheim is a commune in northeastern France’s Alsace region, known as a historic wine-producing village and gateway to the area’s renowned vineyards and scenic countryside.
-
B.
Schweinheim
Schweinheim is a residential district within the Bad Godesberg borough of Bonn in western Germany.
-
C.
Bergheim
Bergheim is a municipality in the Austrian state of Salzburg, located just north of the city of Salzburg and known for its suburban character and proximity to the regional capital.
-
D.
Schaafheim
Schaafheim is a municipality in the state of Hesse in central Germany.
-
E.
Mergentheim
Mergentheim is a historic town in southern Germany best known as the former main seat of the Teutonic Order and for its well-preserved medieval and baroque architecture.
- 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: Schwebheim Triple: [Schweinfurt region, containsTown, Schwebheim]
Generated description
Schwebheim is a small municipality in northern Bavaria, Germany, known for its rural character and proximity to the city of Schweinfurt.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Schwebheim Target entity description: Schwebheim is a small municipality in northern Bavaria, Germany, known for its rural character and proximity to the city of Schweinfurt.
-
A.
Marlenheim
Marlenheim is a commune in northeastern France’s Alsace region, known as a historic wine-producing village and gateway to the area’s renowned vineyards and scenic countryside.
-
B.
Schweinheim
Schweinheim is a residential district within the Bad Godesberg borough of Bonn in western Germany.
-
C.
Bergheim
Bergheim is a municipality in the Austrian state of Salzburg, located just north of the city of Salzburg and known for its suburban character and proximity to the regional capital.
-
D.
Schaafheim
Schaafheim is a municipality in the state of Hesse in central Germany.
-
E.
Mergentheim
Mergentheim is a historic town in southern Germany best known as the former main seat of the Teutonic Order and for its well-preserved medieval and baroque architecture.
- 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_69c687ed8a9c81908bb671717cb192ef |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6af7fc054819099a2e58cefd8fed7 |
completed | March 27, 2026, 4:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7006cf9e881908a7cb7a8209ed7d2 |
completed | March 27, 2026, 10:10 p.m. |
| NEDg | Description generation | batch_69c705d7059c8190a8b5e39cc2a2cde9 |
completed | March 27, 2026, 10:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7063c496c8190a5b2fa40cb4c6768 |
completed | March 27, 2026, 10:35 p.m. |
Created at: March 27, 2026, 1:58 p.m.