Triple
T4163171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U3 |
E91577
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Sündersbühl
Sündersbühl is a district in Nuremberg, Germany, served by the city’s U3 underground line.
|
E416698
|
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: Sündersbühl | Statement: [U3, hasStation, Sündersbühl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sündersbühl Context triple: [U3, hasStation, Sündersbühl]
-
A.
Dinkelsbühl
Dinkelsbühl is a well-preserved medieval town in Bavaria, Germany, renowned for its intact city walls, historic half-timbered houses, and picturesque old town.
-
B.
Schwibbogen
A Schwibbogen is a traditional German decorative candle arch, typically made of wood and displayed in windows during the Christmas season, especially in the Ore Mountains region.
-
C.
Tirschenreuth
Tirschenreuth is a town in northeastern Bavaria, Germany, known for its historic town center and surrounding lake and pond landscapes.
-
D.
Olbernhau
Olbernhau is a town in Germany’s Ore Mountains renowned for its traditional woodcraft industry, especially the production of Schwibbogen candle arches and other Christmas decorations.
-
E.
Marienberg
Marienberg is a historic mining town in Saxony, Germany, known for its Renaissance-era planned layout and location in the central Ore Mountains.
- 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: Sündersbühl Triple: [U3, hasStation, Sündersbühl]
Generated description
Sündersbühl is a district in Nuremberg, Germany, served by the city’s U3 underground line.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sündersbühl Target entity description: Sündersbühl is a district in Nuremberg, Germany, served by the city’s U3 underground line.
-
A.
Dinkelsbühl
Dinkelsbühl is a well-preserved medieval town in Bavaria, Germany, renowned for its intact city walls, historic half-timbered houses, and picturesque old town.
-
B.
Schwibbogen
A Schwibbogen is a traditional German decorative candle arch, typically made of wood and displayed in windows during the Christmas season, especially in the Ore Mountains region.
-
C.
Tirschenreuth
Tirschenreuth is a town in northeastern Bavaria, Germany, known for its historic town center and surrounding lake and pond landscapes.
-
D.
Olbernhau
Olbernhau is a town in Germany’s Ore Mountains renowned for its traditional woodcraft industry, especially the production of Schwibbogen candle arches and other Christmas decorations.
-
E.
Marienberg
Marienberg is a historic mining town in Saxony, Germany, known for its Renaissance-era planned layout and location in the central Ore Mountains.
- 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_69aed9626ebc8190a39de631788bea3e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02a811608190aff8b663498711e8 |
completed | March 9, 2026, 5:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f456bf88190b9b8678476ac3803 |
completed | March 14, 2026, 3:31 p.m. |
| NEDg | Description generation | batch_69b57fe89ed0819089d7e56568755b1c |
completed | March 14, 2026, 3:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5805cb7e88190b2f6ed6a18de9319 |
completed | March 14, 2026, 3:35 p.m. |
Created at: March 9, 2026, 3:44 p.m.