Triple
T20098957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zollernalbkreis |
E496480
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Grosselfingen
Grosselfingen is a small municipality in the Zollernalb district of Baden-Württemberg in southwestern Germany.
|
E1447173
|
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: Grosselfingen | Statement: [Zollernalbkreis, contains, Grosselfingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grosselfingen Context triple: [Zollernalbkreis, contains, Grosselfingen]
-
A.
Effingen
Effingen is a small Swiss village and former municipality in the canton of Aargau, known for its rural character and location near the Jura Mountains.
-
B.
Gechingen
Gechingen is a small municipality in the German state of Baden-Württemberg, situated in the northern Black Forest region.
-
C.
Engstingen
Engstingen is a municipality in the state of Baden-Württemberg in southwestern Germany, situated on the Swabian Alb plateau.
-
D.
Gündlingen
Gündlingen is a village and district of the town Breisach am Rhein in the state of Baden-Württemberg in southwestern Germany.
-
E.
Gernsbach
Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
- 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: Grosselfingen Triple: [Zollernalbkreis, contains, Grosselfingen]
Generated description
Grosselfingen is a small municipality in the Zollernalb district of Baden-Württemberg in southwestern Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Grosselfingen Target entity description: Grosselfingen is a small municipality in the Zollernalb district of Baden-Württemberg in southwestern Germany.
-
A.
Effingen
Effingen is a small Swiss village and former municipality in the canton of Aargau, known for its rural character and location near the Jura Mountains.
-
B.
Gechingen
Gechingen is a small municipality in the German state of Baden-Württemberg, situated in the northern Black Forest region.
-
C.
Engstingen
Engstingen is a municipality in the state of Baden-Württemberg in southwestern Germany, situated on the Swabian Alb plateau.
-
D.
Gündlingen
Gündlingen is a village and district of the town Breisach am Rhein in the state of Baden-Württemberg in southwestern Germany.
-
E.
Gernsbach
Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
- 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_69da626eee3881909f3454986d4a6511 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6666e306c81909c0ef617e0f6fccf |
completed | April 20, 2026, 5:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08e038bca8819086f1c4bfaa0a588d |
completed | May 16, 2026, 9:23 p.m. |
| NEDg | Description generation | batch_6a08e12d0d8c81909527575f628ec2d2 |
completed | May 16, 2026, 9:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08e1a7f16c8190af9a1dde4263e21d |
completed | May 16, 2026, 9:29 p.m. |
Created at: April 11, 2026, 11:26 p.m.