Triple
T12418753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heilbronn |
E296707
|
entity |
| Predicate | regionallyKnownAs |
P14444
|
FINISHED |
| Object |
Käthchenstadt
Käthchenstadt is a regional nickname for the German city of Heilbronn, referencing the famous play "Das Käthchen von Heilbronn" by Heinrich von Kleist.
|
E984831
|
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: Käthchenstadt | Statement: [Heilbronn, regionallyKnownAs, Käthchenstadt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Käthchenstadt Context triple: [Heilbronn, regionallyKnownAs, Käthchenstadt]
-
A.
Seelingstädt
Seelingstädt is a village and subdivision of the town of Trebsen in the German state of Saxony.
-
B.
Dinkelscherben
Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
-
C.
Burgkunstadt
Burgkunstadt is a small Bavarian town in northern Germany known for its historic center and location in the Upper Franconia region.
-
D.
Leutenberg
Leutenberg is a small town in the German state of Thuringia, known for its location in the Thuringian Slate Mountains and its historical sites.
-
E.
Dornstadt
Dornstadt is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, located near the city of Ulm.
- 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: Käthchenstadt Triple: [Heilbronn, regionallyKnownAs, Käthchenstadt]
Generated description
Käthchenstadt is a regional nickname for the German city of Heilbronn, referencing the famous play "Das Käthchen von Heilbronn" by Heinrich von Kleist.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Käthchenstadt Target entity description: Käthchenstadt is a regional nickname for the German city of Heilbronn, referencing the famous play "Das Käthchen von Heilbronn" by Heinrich von Kleist.
-
A.
Seelingstädt
Seelingstädt is a village and subdivision of the town of Trebsen in the German state of Saxony.
-
B.
Dinkelscherben
Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
-
C.
Burgkunstadt
Burgkunstadt is a small Bavarian town in northern Germany known for its historic center and location in the Upper Franconia region.
-
D.
Leutenberg
Leutenberg is a small town in the German state of Thuringia, known for its location in the Thuringian Slate Mountains and its historical sites.
-
E.
Dornstadt
Dornstadt is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, located near the city of Ulm.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d6efd748190a5d9396a343e41e1 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f002b7c81909ee9d4ea3ea6d5f2 |
completed | May 2, 2026, 6:14 p.m. |
| NEDg | Description generation | batch_69f640874a0481908d9203b48304d866 |
completed | May 2, 2026, 6:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f641287f888190bc7000c256c362d3 |
completed | May 2, 2026, 6:23 p.m. |
Created at: April 8, 2026, 9:55 p.m.