Triple
T12433692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cabaret Voltaire |
E297091
|
entity |
| Predicate | district |
P2709
|
FINISHED |
| Object |
Niederdorf
Niederdorf is a historic, nightlife-rich quarter in Zurich’s Old Town known for its narrow medieval streets, bars, restaurants, and cultural venues.
|
E1005300
|
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: Niederdorf | Statement: [Cabaret Voltaire, district, Niederdorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Niederdorf Context triple: [Cabaret Voltaire, district, Niederdorf]
-
A.
Gneixendorf
Gneixendorf is a village and cadastral community that forms part of the city of Krems an der Donau in Lower Austria.
-
B.
Perasdorf
Perasdorf is a small municipality in the Straubing-Bogen district of Lower Bavaria, Germany.
-
C.
Pottendorf
Pottendorf is a market town in Lower Austria known for its historic castle and location within the Baden district.
-
D.
Nițchidorf
Nițchidorf is a village in Timiș County, western Romania, known as the birthplace of Nobel Prize–winning author Herta Müller.
-
E.
Biendorf
Biendorf is a small municipality in northern Germany notable as the birthplace of German Field Marshal Helmuth von Moltke the Younger.
- 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: Niederdorf Triple: [Cabaret Voltaire, district, Niederdorf]
Generated description
Niederdorf is a historic, nightlife-rich quarter in Zurich’s Old Town known for its narrow medieval streets, bars, restaurants, and cultural venues.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Niederdorf Target entity description: Niederdorf is a historic, nightlife-rich quarter in Zurich’s Old Town known for its narrow medieval streets, bars, restaurants, and cultural venues.
-
A.
Gneixendorf
Gneixendorf is a village and cadastral community that forms part of the city of Krems an der Donau in Lower Austria.
-
B.
Perasdorf
Perasdorf is a small municipality in the Straubing-Bogen district of Lower Bavaria, Germany.
-
C.
Pottendorf
Pottendorf is a market town in Lower Austria known for its historic castle and location within the Baden district.
-
D.
Nițchidorf
Nițchidorf is a village in Timiș County, western Romania, known as the birthplace of Nobel Prize–winning author Herta Müller.
-
E.
Biendorf
Biendorf is a small municipality in northern Germany notable as the birthplace of German Field Marshal Helmuth von Moltke the Younger.
- 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_69d94d804c2c819082f2f86edcbb50de |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ea3ec588190bca355953267578f |
completed | May 2, 2026, 11:54 p.m. |
| NEDg | Description generation | batch_69f6902f138c8190a94a01c1fbb30b57 |
completed | May 3, 2026, midnight |
| NED2 | Entity disambiguation (via description) | batch_69f69138b40881909e9c74d6d922e1f3 |
completed | May 3, 2026, 12:05 a.m. |
Created at: April 8, 2026, 9:55 p.m.