Triple
T6624504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schweinfurt region |
E149760
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Lülsfeld
Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
|
E639123
|
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: Lülsfeld | Statement: [Schweinfurt region, containsTown, Lülsfeld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lülsfeld Context triple: [Schweinfurt region, containsTown, Lülsfeld]
-
A.
Lichtenfels
Lichtenfels is a town in the Upper Franconia region of Bavaria, Germany, known for its basket-making tradition and historic architecture.
-
B.
Raesfeld
Raesfeld is a municipality in western Germany’s North Rhine-Westphalia, known for its historic moated castle and rural surroundings.
-
C.
Hasselfelde
Hasselfelde is a small town in the Harz region of central Germany, now incorporated into the municipality of Oberharz am Brocken.
-
D.
Hersbruck
Hersbruck is a small historic town in the Franconian region of Bavaria, Germany, known for its picturesque setting in the Pegnitz Valley and traditional Bavarian architecture.
-
E.
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.
- 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: Lülsfeld Triple: [Schweinfurt region, containsTown, Lülsfeld]
Generated description
Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lülsfeld Target entity description: Lülsfeld is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
-
A.
Lichtenfels
Lichtenfels is a town in the Upper Franconia region of Bavaria, Germany, known for its basket-making tradition and historic architecture.
-
B.
Raesfeld
Raesfeld is a municipality in western Germany’s North Rhine-Westphalia, known for its historic moated castle and rural surroundings.
-
C.
Hasselfelde
Hasselfelde is a small town in the Harz region of central Germany, now incorporated into the municipality of Oberharz am Brocken.
-
D.
Hersbruck
Hersbruck is a small historic town in the Franconian region of Bavaria, Germany, known for its picturesque setting in the Pegnitz Valley and traditional Bavarian architecture.
-
E.
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.
- 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_69c7880545c4819091979008c84b3325 |
completed | March 28, 2026, 7:49 a.m. |
| NEDg | Description generation | batch_69c78b712710819086ce345f9aa74def |
completed | March 28, 2026, 8:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c78bd828d4819085d0959e053b7403 |
completed | March 28, 2026, 8:05 a.m. |
Created at: March 27, 2026, 1:58 p.m.