Triple
T16479810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Breisgau-Hochschwarzwald |
E400283
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Löffingen
Löffingen is a small town in southwestern Germany’s Black Forest region, known for its historic town center and scenic natural surroundings.
|
E1231638
|
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: Löffingen | Statement: [Breisgau-Hochschwarzwald, contains, Löffingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Löffingen Context triple: [Breisgau-Hochschwarzwald, contains, Löffingen]
-
A.
Röfingen
Röfingen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
B.
Pfullendorf
Pfullendorf is a historic town in the state of Baden-Württemberg in southern Germany, known for its well-preserved medieval old town.
-
C.
Lautlingen
Lautlingen is a village in the Zollernalb district of Baden-Württemberg, Germany, now incorporated as a district of the town of Albstadt.
-
D.
Pfullingen
Pfullingen is a small town in the state of Baden-Württemberg in southwestern Germany, situated near the Swabian Jura and close to the city of Reutlingen.
-
E.
Wehringen
Wehringen is a small municipality in Bavaria, Germany, situated in the region surrounding the city of Augsburg.
- 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: Löffingen Triple: [Breisgau-Hochschwarzwald, contains, Löffingen]
Generated description
Löffingen is a small town in southwestern Germany’s Black Forest region, known for its historic town center and scenic natural surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Löffingen Target entity description: Löffingen is a small town in southwestern Germany’s Black Forest region, known for its historic town center and scenic natural surroundings.
-
A.
Röfingen
Röfingen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
B.
Pfullendorf
Pfullendorf is a historic town in the state of Baden-Württemberg in southern Germany, known for its well-preserved medieval old town.
-
C.
Lautlingen
Lautlingen is a village in the Zollernalb district of Baden-Württemberg, Germany, now incorporated as a district of the town of Albstadt.
-
D.
Pfullingen
Pfullingen is a small town in the state of Baden-Württemberg in southwestern Germany, situated near the Swabian Jura and close to the city of Reutlingen.
-
E.
Wehringen
Wehringen is a small municipality in Bavaria, Germany, situated in the region surrounding the city of Augsburg.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e01f6c88190b75a0d6c94786426 |
completed | April 18, 2026, 7:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a50665d081908c07fe3cb59088b3 |
completed | May 10, 2026, 3:32 p.m. |
| NEDg | Description generation | batch_6a00a59d9e208190a58dccc87af7a919 |
completed | May 10, 2026, 3:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00a5f3ddbc8190b3138f94a9c0aec9 |
completed | May 10, 2026, 3:36 p.m. |
Created at: April 10, 2026, 5:13 a.m.