Triple
T9859008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coburg district |
E239658
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Rödental
Rödental is a small town in northern Bavaria, Germany, known for its location near Coburg and its traditional Franconian character.
|
E836954
|
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: Rödental | Statement: [Coburg district, contains, Rödental]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rödental Context triple: [Coburg district, contains, Rödental]
-
A.
Schuttertal
Schuttertal is a rural municipality in southwestern Germany’s Baden-Württemberg region, situated within the Ortenaukreis district and known for its scenic valleys and Black Forest landscapes.
-
B.
Rauental
Rauental is a district of the German town of Rastatt in the state of Baden-Württemberg.
-
C.
Riederau
Riederau is a small lakeside district of Dießen am Ammersee in Bavaria, Germany, known for its scenic location on the shores of Lake Ammersee.
-
D.
Löstertal
Löstertal is a locality within the town of Wadern in the Saarland region of Germany, known for its rural character and scenic surroundings.
-
E.
Klostertal
Klostertal is a scenic alpine valley in the Austrian state of Vorarlberg, known for its mountain landscapes, ski areas, and access to the Arlberg region.
- 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: Rödental Triple: [Coburg district, contains, Rödental]
Generated description
Rödental is a small town in northern Bavaria, Germany, known for its location near Coburg and its traditional Franconian character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rödental Target entity description: Rödental is a small town in northern Bavaria, Germany, known for its location near Coburg and its traditional Franconian character.
-
A.
Schuttertal
Schuttertal is a rural municipality in southwestern Germany’s Baden-Württemberg region, situated within the Ortenaukreis district and known for its scenic valleys and Black Forest landscapes.
-
B.
Rauental
Rauental is a district of the German town of Rastatt in the state of Baden-Württemberg.
-
C.
Riederau
Riederau is a small lakeside district of Dießen am Ammersee in Bavaria, Germany, known for its scenic location on the shores of Lake Ammersee.
-
D.
Löstertal
Löstertal is a locality within the town of Wadern in the Saarland region of Germany, known for its rural character and scenic surroundings.
-
E.
Klostertal
Klostertal is a scenic alpine valley in the Austrian state of Vorarlberg, known for its mountain landscapes, ski areas, and access to the Arlberg region.
- 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_69ca84e6493081909cf58c8d42ea856b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb39b06b48190ab53ff00ff0513ca |
completed | April 2, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d281b9254c81908d5acbdb42196ab1 |
completed | April 5, 2026, 3:37 p.m. |
| NEDg | Description generation | batch_69d2834f6d488190812f91a5b4971c1e |
completed | April 5, 2026, 3:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d28432d900819091ff0d324a6bb28a |
completed | April 5, 2026, 3:48 p.m. |
Created at: March 30, 2026, 8:35 p.m.